Prioritized deleting of slices stored in a dispersed storage network

ABSTRACT

A method begins, as data objects are ingested, by determining, for each of some of the data objects, a priority indicator to produce a listing of priority indicators. The method continues for a data object by determining encoding parameters based on a corresponding priority indicator. The method continues by encoding the data object in accordance with the encoding parameters to produce a plurality of sets of encoded data slices and storing them. The method continues by identifying a first data object for analysis based on a corresponding priority indicator and an analysis priority. The method continues by decoding a plurality of sets of encoded data slices to recover the first data object and analyzing it in accordance with analysis criteria to determine its relevancy. The method continues by issuing a command to delete the plurality of sets of encoded data slices when the relevancy is below a threshold.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility patent application claims priority pursuant to35 U.S.C. §120 as a continuation of U.S. Utility application Ser. No.13/464,846, entitled “PRIORITIZED DELETING OF SLICES STORED IN ADISPERSED STORAGE NETWORK”, filed May 4, 2012, issuing as U.S. Pat. No.8,756,480 on Jun. 17, 2014, which claims priority pursuant to 35 U.S.C.§119(e) to U.S. Provisional Application No. 61/493,825, entitled“ACCESSING DATA IN A DISPERSED STORAGE NETWORK”, filed Jun. 6, 2011, allof which are hereby incorporated herein by reference in their entiretyand made part of the present U.S. Utility patent application for allpurposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

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INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

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BACKGROUND OF THE INVENTION

1. Technical Field of the Invention

This invention relates generally to computing systems and moreparticularly to data storage solutions within such computing systems.

2. Description of Related Art

Computers are known to communicate, process, and store data. Suchcomputers range from wireless smart phones to data centers that supportmillions of web searches, stock trades, or on-line purchases every day.In general, a computing system generates data and/or manipulates datafrom one form into another. For instance, an image sensor of thecomputing system generates raw picture data and, using an imagecompression program (e.g., JPEG, MPEG, etc.), the computing systemmanipulates the raw picture data into a standardized compressed image.

With continued advances in processing speed and communication speed,computers are capable of processing real time multimedia data forapplications ranging from simple voice communications to streaming highdefinition video. As such, general-purpose information appliances arereplacing purpose-built communications devices (e.g., a telephone). Forexample, smart phones can support telephony communications but they arealso capable of text messaging and accessing the internet to performfunctions including email, web browsing, remote applications access, andmedia communications (e.g., telephony voice, image transfer, musicfiles, video files, real time video streaming. etc.).

Each type of computer is constructed and operates in accordance with oneor more communication, processing, and storage standards. As a result ofstandardization and with advances in technology, more and moreinformation content is being converted into digital formats. Forexample, more digital cameras are now being sold than film cameras, thusproducing more digital pictures. As another example, web-basedprogramming is becoming an alternative to over the air televisionbroadcasts and/or cable broadcasts. As further examples, papers, books,video entertainment, home video, etc. are now being stored digitally,which increases the demand on the storage function of computers.

A typical computer storage system includes one or more memory devicesaligned with the needs of the various operational aspects of thecomputer's processing and communication functions. Generally, theimmediacy of access dictates what type of memory device is used. Forexample, random access memory (RAM) memory can be accessed in any randomorder with a constant response time, thus it is typically used for cachememory and main memory. By contrast, memory device technologies thatrequire physical movement such as magnetic disks, tapes, and opticaldiscs, have a variable response time as the physical movement can takelonger than the data transfer, thus they are typically used forsecondary memory (e.g., hard drive, backup memory, etc.).

A computer's storage system will be compliant with one or more computerstorage standards that include, but are not limited to, network filesystem (NFS), flash file system (FFS), disk file system (DFS), smallcomputer system interface (SCSI), internet small computer systeminterface (iSCSI), file transfer protocol (FTP), and web-baseddistributed authoring and versioning (WebDAV). These standards specifythe data storage format (e.g., files, data objects, data blocks,directories, etc.) and interfacing between the computer's processingfunction and its storage system, which is a primary function of thecomputer's memory controller.

Despite the standardization of the computer and its storage system,memory devices fail; especially commercial grade memory devices thatutilize technologies incorporating physical movement (e.g., a discdrive). For example, it is fairly common for a disc drive to routinelysuffer from bit level corruption and to completely fail after threeyears of use. One solution is to a higher-grade disc drive, which addssignificant cost to a computer.

Another solution is to utilize multiple levels of redundant disc drivesto replicate the data into two or more copies. One such redundant driveapproach is called redundant array of independent discs (RAID). In aRAID device, a RAID controller adds parity data to the original databefore storing it across the array. The parity data is calculated fromthe original data such that the failure of a disc will not result in theloss of the original data. For example, RAID 5 uses three discs toprotect data from the failure of a single disc. The parity data, andassociated redundancy overhead data, reduces the storage capacity ofthree independent discs by one third (e.g., n−1=capacity). RAID 6 canrecover from a loss of two discs and requires a minimum of four discswith a storage capacity of n−2.

While RAID addresses the memory device failure issue, it is not withoutits own failures issues that affect its effectiveness, efficiency andsecurity. For instance, as more discs are added to the array, theprobability of a disc failure increases, which increases the demand formaintenance. For example, when a disc fails, it needs to be manuallyreplaced before another disc fails and the data stored in the RAIDdevice is lost. To reduce the risk of data loss, data on a RAID deviceis typically copied on to one or more other RAID devices. While thisaddresses the loss of data issue, it raises a security issue sincemultiple copies of data are available, which increases the chances ofunauthorized access. Further, as the amount of data being stored grows,the overhead of RAID devices becomes a non-trivial efficiency issue.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a computingsystem in accordance with the present invention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an embodiment of a distributedstorage processing unit in accordance with the present invention;

FIG. 4 is a schematic block diagram of an embodiment of a grid module inaccordance with the present invention;

FIG. 5 is a diagram of an example embodiment of error coded data slicecreation in accordance with the present invention;

FIG. 6 is a schematic block diagram of another embodiment of a computingsystem in accordance with the present invention;

FIG. 7A is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 7B is a flowchart illustrating an example of distributingmulti-media content in accordance with the present invention;

FIG. 8A is a flowchart illustrating another example of facilitatingpartial content downloading in accordance with the present invention;

FIG. 8B is a flowchart illustrating an example of acquiring multi-mediacontent in accordance with the present invention;

FIG. 9 is a flowchart illustrating an example of staging content fordownloading in accordance with the present invention;

FIG. 10A is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 10B is a flowchart illustrating another example of acquiringmulti-media content in accordance with the present invention;

FIG. 11 is a flowchart illustrating an example of maintainingtemporarily stored encoded data slices in accordance with the presentinvention;

FIG. 12A is a schematic block diagram of an embodiment of a wirelessuser device in accordance with the present invention;

FIG. 12B is a flowchart illustrating an example of communicating encodeddata slices via a wireless connection in accordance with the presentinvention;

FIG. 13 is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 14A is a schematic block diagram of another embodiment of acomputing system in accordance with the present invention;

FIG. 14B is a flowchart illustrating an example of deleting data storedin a dispersed storage network (DSN) in accordance with the presentinvention;

FIG. 15 is a flowchart illustrating an example of deleting data storedin a dispersed storage network (DSN) in accordance with the presentinvention;

FIG. 16 is a flowchart illustrating an example of rebuilding data storedin a dispersed storage network (DSN) in accordance with the presentinvention;

FIG. 17A is a flowchart illustrating another example of rebuilding datastored in a dispersed storage network (DSN) in accordance with thepresent invention; and

FIG. 17B is a flowchart illustrating another example of rebuilding datastored in a dispersed storage network (DSN) in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of a computing system 10 thatincludes one or more of a first type of user devices 12, one or more ofa second type of user devices 14, at least one distributed storage (DS)processing unit 16, at least one DS managing unit 18, at least onestorage integrity processing unit 20, and a distributed storage network(DSN) memory 22 coupled via a network 24. The network 24 may include oneor more wireless and/or wire lined communication systems; one or moreprivate intranet systems and/or public internet systems; and/or one ormore local area networks (LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of distributed storage (DS) units36 for storing data of the system. Each of the DS units 36 includes aprocessing module and memory and may be located at a geographicallydifferent site than the other DS units (e.g., one in Chicago, one inMilwaukee, etc.).

Each of the user devices 12-14, the DS processing unit 16, the DSmanaging unit 18, and the storage integrity processing unit 20 may be aportable computing device (e.g., a social networking device, a gamingdevice, a cell phone, a smart phone, a personal digital assistant, adigital music player, a digital video player, a laptop computer, ahandheld computer, a video game controller, and/or any other portabledevice that includes a computing core) and/or a fixed computing device(e.g., a personal computer, a computer server, a cable set-top box, asatellite receiver, a television set, a printer, a fax machine, homeentertainment equipment, a video game console, and/or any type of homeor office computing equipment). Such a portable or fixed computingdevice includes a computing core 26 and one or more interfaces 30, 32,and/or 33. An embodiment of the computing core 26 will be described withreference to FIG. 2.

With respect to the interfaces, each of the interfaces 30, 32, and 33includes software and/or hardware to support one or more communicationlinks via the network 24 indirectly and/or directly. For example,interfaces 30 support a communication link (wired, wireless, direct, viaa LAN, via the network 24, etc.) between the first type of user device14 and the DS processing unit 16. As another example, DSN interface 32supports a plurality of communication links via the network 24 betweenthe DSN memory 22 and the DS processing unit 16, the first type of userdevice 12, and/or the storage integrity processing unit 20. As yetanother example, interface 33 supports a communication link between theDS managing unit 18 and any one of the other devices and/or units 12,14, 16, 20, and/or 22 via the network 24.

In general and with respect to data storage, the system 10 supportsthree primary functions: distributed network data storage management,distributed data storage and retrieval, and data storage integrityverification. In accordance with these three primary functions, data canbe distributedly stored in a plurality of physically different locationsand subsequently retrieved in a reliable and secure manner regardless offailures of individual storage devices, failures of network equipment,the duration of storage, the amount of data being stored, attempts athacking the data, etc.

The DS managing unit 18 performs distributed network data storagemanagement functions, which include establishing distributed datastorage parameters, performing network operations, performing networkadministration, and/or performing network maintenance. The DS managingunit 18 establishes the distributed data storage parameters (e.g.,allocation of virtual DSN memory space, distributed storage parameters,security parameters, billing information, user profile information,etc.) for one or more of the user devices 12-14 (e.g., established forindividual devices, established for a user group of devices, establishedfor public access by the user devices, etc.). For example, the DSmanaging unit 18 coordinates the creation of a vault (e.g., a virtualmemory block) within the DSN memory 22 for a user device (for a group ofdevices, or for public access). The DS managing unit 18 also determinesthe distributed data storage parameters for the vault. In particular,the DS managing unit 18 determines a number of slices (e.g., the numberthat a data segment of a data file and/or data block is partitioned intofor distributed storage) and a read threshold value (e.g., the minimumnumber of slices required to reconstruct the data segment).

As another example, the DS managing module 18 creates and stores,locally or within the DSN memory 22, user profile information. The userprofile information includes one or more of authentication information,permissions, and/or the security parameters. The security parameters mayinclude one or more of encryption/decryption scheme, one or moreencryption keys, key generation scheme, and data encoding/decodingscheme.

As yet another example, the DS managing unit 18 creates billinginformation for a particular user, user group, vault access, publicvault access, etc. For instance, the DS managing unit 18 tracks thenumber of times user accesses a private vault and/or public vaults,which can be used to generate a per-access bill. In another instance,the DS managing unit 18 tracks the amount of data stored and/orretrieved by a user device and/or a user group, which can be used togenerate a per-data-amount bill.

The DS managing unit 18 also performs network operations, networkadministration, and/or network maintenance. As at least part ofperforming the network operations and/or administration, the DS managingunit 18 monitors performance of the devices and/or units of the system10 for potential failures, determines the devices and/or unit'sactivation status, determines the devices' and/or units' loading, andany other system level operation that affects the performance level ofthe system 10. For example, the DS managing unit 18 receives andaggregates network management alarms, alerts, errors, statusinformation, performance information, and messages from the devices12-14 and/or the units 16, 20, 22. For example, the DS managing unit 18receives a simple network management protocol (SNMP) message regardingthe status of the DS processing unit 16.

The DS managing unit 18 performs the network maintenance by identifyingequipment within the system 10 that needs replacing, upgrading,repairing, and/or expanding. For example, the DS managing unit 18determines that the DSN memory 22 needs more DS units 36 or that one ormore of the DS units 36 needs updating.

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a user device 12-14. For instance, if asecond type of user device 14 has a data file 38 and/or data block 40 tostore in the DSN memory 22, it send the data file 38 and/or data block40 to the DS processing unit 16 via its interface 30. As will bedescribed in greater detail with reference to FIG. 2, the interface 30functions to mimic a conventional operating system (OS) file systeminterface (e.g., network file system (NFS), flash file system (FFS),disk file system (DFS), file transfer protocol (FTP), web-baseddistributed authoring and versioning (WebDAV), etc.) and/or a blockmemory interface (e.g., small computer system interface (SCSI), internetsmall computer system interface (iSCSI), etc.). In addition, theinterface 30 may attach a user identification code (ID) to the data file38 and/or data block 40.

The DS processing unit 16 receives the data file 38 and/or data block 40via its interface 30 and performs a distributed storage (DS) process 34thereon (e.g., an error coding dispersal storage function). The DSprocessing 34 begins by partitioning the data file 38 and/or data block40 into one or more data segments, which is represented as Y datasegments. For example, the DS processing 34 may partition the data file38 and/or data block 40 into a fixed byte size segment (e.g., 2¹ to2^(n) bytes, where n=>2) or a variable byte size (e.g., change byte sizefrom segment to segment, or from groups of segments to groups ofsegments, etc.).

For each of the Y data segments, the DS processing 34 error encodes(e.g., forward error correction (FEC), information dispersal algorithm,or error correction coding) and slices (or slices then error encodes)the data segment into a plurality of error coded (EC) data slices 42-48,which is represented as X slices per data segment. The number of slices(X) per segment, which corresponds to a number of pillars n, is set inaccordance with the distributed data storage parameters and the errorcoding scheme. For example, if a Reed-Solomon (or other FEC scheme) isused in an n/k system, then a data segment is divided into n slices,where k number of slices is needed to reconstruct the original data(i.e., k is the threshold). As a few specific examples, the n/k factormay be 5/3; 6/4; 8/6; 8/5; 16/10.

For each slice 42-48, the DS processing unit 16 creates a unique slicename and appends it to the corresponding slice 42-48. The slice nameincludes universal DSN memory addressing routing information (e.g.,virtual memory addresses in the DSN memory 22) and user-specificinformation (e.g., user ID, file name, data block identifier, etc.).

The DS processing unit 16 transmits the plurality of EC slices 42-48 toa plurality of DS units 36 of the DSN memory 22 via the DSN interface 32and the network 24. The DSN interface 32 formats each of the slices fortransmission via the network 24. For example, the DSN interface 32 mayutilize an internet protocol (e.g., TCP/IP, etc.) to packetize theslices 42-48 for transmission via the network 24.

The number of DS units 36 receiving the slices 42-48 is dependent on thedistributed data storage parameters established by the DS managing unit18. For example, the DS managing unit 18 may indicate that each slice isto be stored in a different DS unit 36. As another example, the DSmanaging unit 18 may indicate that like slice numbers of different datasegments are to be stored in the same DS unit 36. For example, the firstslice of each of the data segments is to be stored in a first DS unit36, the second slice of each of the data segments is to be stored in asecond DS unit 36, etc. In this manner, the data is encoded anddistributedly stored at physically diverse locations to improved datastorage integrity and security.

Each DS unit 36 that receives a slice 42-48 for storage translates thevirtual DSN memory address of the slice into a local physical addressfor storage. Accordingly, each DS unit 36 maintains a virtual tophysical memory mapping to assist in the storage and retrieval of data.

The first type of user device 12 performs a similar function to storedata in the DSN memory 22 with the exception that it includes the DSprocessing. As such, the device 12 encodes and slices the data fileand/or data block it has to store. The device then transmits the slices11 to the DSN memory via its DSN interface 32 and the network 24.

For a second type of user device 14 to retrieve a data file or datablock from memory, it issues a read command via its interface 30 to theDS processing unit 16. The DS processing unit 16 performs the DSprocessing 34 to identify the DS units 36 storing the slices of the datafile and/or data block based on the read command. The DS processing unit16 may also communicate with the DS managing unit 18 to verify that theuser device 14 is authorized to access the requested data.

Assuming that the user device is authorized to access the requesteddata, the DS processing unit 16 issues slice read commands to at least athreshold number of the DS units 36 storing the requested data (e.g., toat least 10 DS units for a 16/10 error coding scheme). Each of the DSunits 36 receiving the slice read command, verifies the command,accesses its virtual to physical memory mapping, retrieves the requestedslice, or slices, and transmits it to the DS processing unit 16.

Once the DS processing unit 16 has received a read threshold number ofslices for a data segment, it performs an error decoding function andde-slicing to reconstruct the data segment. When Y number of datasegments has been reconstructed, the DS processing unit 16 provides thedata file 38 and/or data block 40 to the user device 14. Note that thefirst type of user device 12 performs a similar process to retrieve adata file and/or data block.

The storage integrity processing unit 20 performs the third primaryfunction of data storage integrity verification. In general, the storageintegrity processing unit 20 periodically retrieves slices 45, and/orslice names, of a data file or data block of a user device to verifythat one or more slices have not been corrupted or lost (e.g., the DSunit failed). The retrieval process mimics the read process previouslydescribed.

If the storage integrity processing unit 20 determines that one or moreslices is corrupted or lost, it rebuilds the corrupted or lost slice(s)in accordance with the error coding scheme. The storage integrityprocessing unit 20 stores the rebuild slice, or slices, in theappropriate DS unit(s) 36 in a manner that mimics the write processpreviously described.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,at least one IO device interface module 62, a read only memory (ROM)basic input output system (BIOS) 64, and one or more memory interfacemodules. The memory interface module(s) includes one or more of auniversal serial bus (USB) interface module 66, a host bus adapter (HBA)interface module 68, a network interface module 70, a flash interfacemodule 72, a hard drive interface module 74, and a DSN interface module76. Note the DSN interface module 76 and/or the network interface module70 may function as the interface 30 of the user device 14 of FIG. 1.Further note that the IO device interface module 62 and/or the memoryinterface modules may be collectively or individually referred to as IOports.

FIG. 3 is a schematic block diagram of an embodiment of a dispersedstorage (DS) processing module 34 of user device 12 and/or of the DSprocessing unit 16. The DS processing module 34 includes a gatewaymodule 78, an access module 80, a grid module 82, and a storage module84. The DS processing module 34 may also include an interface 30 and theDSnet interface 32 or the interfaces 68 and/or 70 may be part of user 12or of the DS processing unit 14. The DS processing module 34 may furtherinclude a bypass/feedback path between the storage module 84 to thegateway module 78. Note that the modules 78-84 of the DS processingmodule 34 may be in a single unit or distributed across multiple units.

In an example of storing data, the gateway module 78 receives anincoming data object that includes a user ID field 86, an object namefield 88, and the data field 40 and may also receive correspondinginformation that includes a process identifier (e.g., an internalprocess/application ID), metadata, a file system directory, a blocknumber, a transaction message, a user device identity (ID), a dataobject identifier, a source name, and/or user information. The gatewaymodule 78 authenticates the user associated with the data object byverifying the user ID 86 with the managing unit 18 and/or anotherauthenticating unit.

When the user is authenticated, the gateway module 78 obtains userinformation from the management unit 18, the user device, and/or theother authenticating unit. The user information includes a vaultidentifier, operational parameters, and user attributes (e.g., userdata, billing information, etc.). A vault identifier identifies a vault,which is a virtual memory space that maps to a set of DS storage units36. For example, vault 1 (i.e., user 1's DSN memory space) includeseight DS storage units (X=8 wide) and vault 2 (i.e., user 2's DSN memoryspace) includes sixteen DS storage units (X=16 wide). The operationalparameters may include an error coding algorithm, the width n (number ofpillars X or slices per segment for this vault), a read threshold T, awrite threshold, an encryption algorithm, a slicing parameter, acompression algorithm, an integrity check method, caching settings,parallelism settings, and/or other parameters that may be used to accessthe DSN memory layer.

The gateway module 78 uses the user information to assign a source name35 to the data. For instance, the gateway module 60 determines thesource name 35 of the data object 40 based on the vault identifier andthe data object. For example, the source name may contain a fileidentifier (ID), a vault generation number, a reserved field, and avault identifier (ID). As another example, the gateway module 78 maygenerate the file ID based on a hash function of the data object 40.Note that the gateway module 78 may also perform message conversion,protocol conversion, electrical conversion, optical conversion, accesscontrol, user identification, user information retrieval, trafficmonitoring, statistics generation, configuration, management, and/orsource name determination.

The access module 80 receives the data object 40 and creates a series ofdata segments 1 through Y 90-92 in accordance with a data storageprotocol (e.g., file storage system, a block storage system, and/or anaggregated block storage system). The number of segments Y may be chosenor randomly assigned based on a selected segment size and the size ofthe data object. For example, if the number of segments is chosen to bea fixed number, then the size of the segments varies as a function ofthe size of the data object. For instance, if the data object is animage file of 4,194,304 eight bit bytes (e.g., 33,554,432 bits) and thenumber of segments Y=131,072, then each segment is 256 bits or 32 bytes.As another example, if segment sized is fixed, then the number ofsegments Y varies based on the size of data object. For instance, if thedata object is an image file of 4,194,304 bytes and the fixed size ofeach segment is 4,096 bytes, the then number of segments Y=1,024. Notethat each segment is associated with the same source name.

The grid module 82 receives the data segments and may manipulate (e.g.,compression, encryption, cyclic redundancy check (CRC), etc.) each ofthe data segments before performing an error coding function of theerror coding dispersal storage function to produce a pre-manipulateddata segment. After manipulating a data segment, if applicable, the gridmodule 82 error encodes (e.g., Reed-Solomon, Convolution encoding,Trellis encoding, etc.) the data segment or manipulated data segmentinto X error coded data slices 42-44.

The value X, or the number of pillars (e.g., X=16), is chosen as aparameter of the error coding dispersal storage function. Otherparameters of the error coding dispersal function include a readthreshold T, a write threshold W, etc. The read threshold (e.g., T=10,when X=16) corresponds to the minimum number of error-free error codeddata slices required to reconstruct the data segment. In other words,the DS processing module 34 can compensate for X-T (e.g., 16−10=6)missing error coded data slices per data segment. The write threshold Wcorresponds to a minimum number of DS storage units that acknowledgeproper storage of their respective data slices before the DS processingmodule indicates proper storage of the encoded data segment. Note thatthe write threshold is greater than or equal to the read threshold for agiven number of pillars (X).

For each data slice of a data segment, the grid module 82 generates aunique slice name 37 and attaches it thereto. The slice name 37 includesa universal routing information field and a vault specific field and maybe 48 bytes (e.g., 24 bytes for each of the universal routinginformation field and the vault specific field). As illustrated, theuniversal routing information field includes a slice index, a vault ID,a vault generation, and a reserved field. The slice index is based onthe pillar number and the vault ID and, as such, is unique for eachpillar (e.g., slices of the same pillar for the same vault for anysegment will share the same slice index). The vault specific fieldincludes a data name, which includes a file ID and a segment number(e.g., a sequential numbering of data segments 1-Y of a simple dataobject or a data block number).

Prior to outputting the error coded data slices of a data segment, thegrid module may perform post-slice manipulation on the slices. Ifenabled, the manipulation includes slice level compression, encryption,CRC, addressing, tagging, and/or other manipulation to improve theeffectiveness of the computing system.

When the error coded data slices of a data segment are ready to beoutputted, the grid module 82 determines which of the DS storage units36 will store the EC data slices based on a dispersed storage memorymapping associated with the user's vault and/or DS storage unitattributes. The DS storage unit attributes may include availability,self-selection, performance history, link speed, link latency,ownership, available DSN memory, domain, cost, a prioritization scheme,a centralized selection message from another source, a lookup table,data ownership, and/or any other factor to optimize the operation of thecomputing system. Note that the number of DS storage units 36 is equalto or greater than the number of pillars (e.g., X) so that no more thanone error coded data slice of the same data segment is stored on thesame DS storage unit 36. Further note that EC data slices of the samepillar number but of different segments (e.g., EC data slice 1 of datasegment 1 and EC data slice 1 of data segment 2) may be stored on thesame or different DS storage units 36.

The storage module 84 performs an integrity check on the outboundencoded data slices and, when successful, identifies a plurality of DSstorage units based on information provided by the grid module 82. Thestorage module 84 then outputs the encoded data slices 1 through X ofeach segment 1 through Y to the DS storage units 36. Each of the DSstorage units 36 stores its EC data slice(s) and maintains a localvirtual DSN address to physical location table to convert the virtualDSN address of the EC data slice(s) into physical storage addresses.

In an example of a read operation, the user device 12 and/or 14 sends aread request to the DS processing unit 14, which authenticates therequest. When the request is authentic, the DS processing unit 14 sendsa read message to each of the DS storage units 36 storing slices of thedata object being read. The slices are received via the DSnet interface32 and processed by the storage module 84, which performs a parity checkand provides the slices to the grid module 82 when the parity check wassuccessful. The grid module 82 decodes the slices in accordance with theerror coding dispersal storage function to reconstruct the data segment.The access module 80 reconstructs the data object from the data segmentsand the gateway module 78 formats the data object for transmission tothe user device.

FIG. 4 is a schematic block diagram of an embodiment of a grid module 82that includes a control unit 73, a pre-slice manipulator 75, an encoder77, a slicer 79, a post-slice manipulator 81, a pre-slice de-manipulator83, a decoder 85, a de-slicer 87, and/or a post-slice de-manipulator 89.Note that the control unit 73 may be partially or completely external tothe grid module 82. For example, the control unit 73 may be part of thecomputing core at a remote location, part of a user device, part of theDS managing unit 18, or distributed amongst one or more DS storageunits.

In an example of write operation, the pre-slice manipulator 75 receivesa data segment 90-92 and a write instruction from an authorized userdevice. The pre-slice manipulator 75 determines if pre-manipulation ofthe data segment 90-92 is required and, if so, what type. The pre-slicemanipulator 75 may make the determination independently or based oninstructions from the control unit 73, where the determination is basedon a computing system-wide predetermination, a table lookup, vaultparameters associated with the user identification, the type of data,security requirements, available DSN memory, performance requirements,and/or other metadata.

Once a positive determination is made, the pre-slice manipulator 75manipulates the data segment 90-92 in accordance with the type ofmanipulation. For example, the type of manipulation may be compression(e.g., Lempel-Ziv-Welch, Huffman, Golomb, fractal, wavelet, etc.),signatures (e.g., Digital Signature Algorithm (DSA), Elliptic Curve DSA,Secure Hash Algorithm, etc.), watermarking, tagging, encryption (e.g.,Data Encryption Standard, Advanced Encryption Standard, etc.), addingmetadata (e.g., time/date stamping, user information, file type, etc.),cyclic redundancy check (e.g., CRC32), and/or other data manipulationsto produce the pre-manipulated data segment.

The encoder 77 encodes the pre-manipulated data segment 92 using aforward error correction (FEC) encoder (and/or other type of erasurecoding and/or error coding) to produce an encoded data segment 94. Theencoder 77 determines which forward error correction algorithm to usebased on a predetermination associated with the user's vault, a timebased algorithm, user direction, DS managing unit direction, controlunit direction, as a function of the data type, as a function of thedata segment 92 metadata, and/or any other factor to determine algorithmtype. The forward error correction algorithm may be Golay,Multidimensional parity, Reed-Solomon, Hamming, Bose Ray ChauduriHocquenghem (BCH), Cauchy-Reed-Solomon, or any other FEC encoder. Notethat the encoder 77 may use a different encoding algorithm for each datasegment 92, the same encoding algorithm for the data segments 92 of adata object, or a combination thereof.

The encoded data segment 94 is of greater size than the data segment 92by the overhead rate of the encoding algorithm by a factor of X/T, whereX is the width or number of slices, and T is the read threshold. In thisregard, the corresponding decoding process can accommodate at most X-Tmissing EC data slices and still recreate the data segment 92. Forexample, if X=16 and T=10, then the data segment 92 will be recoverableas long as 10 or more EC data slices per segment are not corrupted.

The slicer 79 transforms the encoded data segment 94 into EC data slicesin accordance with the slicing parameter from the vault for this userand/or data segment 92. For example, if the slicing parameter is X=16,then the slicer 79 slices each encoded data segment 94 into 16 encodedslices.

The post-slice manipulator 81 performs, if enabled, post-manipulation onthe encoded slices to produce the EC data slices. If enabled, thepost-slice manipulator 81 determines the type of post-manipulation,which may be based on a computing system-wide predetermination,parameters in the vault for this user, a table lookup, the useridentification, the type of data, security requirements, available DSNmemory, performance requirements, control unit directed, and/or othermetadata. Note that the type of post-slice manipulation may includeslice level compression, signatures, encryption, CRC, addressing,watermarking, tagging, adding metadata, and/or other manipulation toimprove the effectiveness of the computing system.

In an example of a read operation, the post-slice de-manipulator 89receives at least a read threshold number of EC data slices and performsthe inverse function of the post-slice manipulator 81 to produce aplurality of encoded slices. The de-slicer 87 de-slices the encodedslices to produce an encoded data segment 94. The decoder 85 performsthe inverse function of the encoder 77 to recapture the data segment90-92. The pre-slice de-manipulator 83 performs the inverse function ofthe pre-slice manipulator 75 to recapture the data segment 90-92.

FIG. 5 is a diagram of an example of slicing an encoded data segment 94by the slicer 79. In this example, the encoded data segment 94 includesthirty-two bits, but may include more or less bits. The slicer 79disperses the bits of the encoded data segment 94 across the EC dataslices in a pattern as shown. As such, each EC data slice does notinclude consecutive bits of the data segment 94 reducing the impact ofconsecutive bit failures on data recovery. For example, if EC data slice2 (which includes bits 1, 5, 9, 13, 17, 25, and 29) is unavailable(e.g., lost, inaccessible, or corrupted), the data segment can bereconstructed from the other EC data slices (e.g., 1, 3 and 4 for a readthreshold of 3 and a width of 4).

FIG. 6 is a schematic block diagram of another embodiment of a computingsystem that includes a plurality of content providers 1-C, a dispersedstorage (DS) processing unit 16, a network 24, a dispersed storagenetwork (DSN) memory 22, a wireless controller 102, a base station 108,a wireless router 104, a distribution server 106, a plurality of userdevices 12, a wireless transceiver 112, a low tier user device 114, anda plurality of wireless user devices 110. Each of the wirelesscontroller 102, the wireless router 104, the distribution server 106,the user device 12, and the wireless user device 110 may include slicememory (SM) 116, which includes a temporary slice memory and anon-temporary slice memory 120.

Each of the content providers 1-C provides content 122 for distributionto the user devices (e.g., low tier user device 114, user device 12,wireless user device 110), where the content 122 includes multimedia,video, movies, music, audio recordings, pictures, sound files, imagefiles, applications, and/or software. A content provider may add acontent descriptor to its content 122, where the content descriptorincludes a content type, a genre type, an artist, a movie type, a musictype, a release date, pricing information, purchase indicatorinformation, a demographic indicator, a favorite syndicator, a qualityrating, and/or an industry rating. Note that the content descriptor maybe embedded in the content 122 or conveyed separately.

In an example of operation, a content provider has content 122 that itdesires to distribute to a plurality of user devices in an efficientmanner. For example, the content provider desired to distribute contenton a release date in an efficient manner (e.g., with as minimal impacton the network and with as minimal delay to the user devices aspractical). In this regard, the content provider provides the content toa DS processing unit 16 prior to, or concurrently with, making thecontent available to the public (e.g., the user devices).

The DS processing unit 16 dispersed storage error encode the content 122to produce a plurality of sets of encoded data slices, where a set ofencoded data slices corresponds to an encoded data segment of thecontent. The DS processing unit sends the slices 11 to the DSN memory 22for storage therein. In addition, the DS processing unit distributes anunreadable portion of the content 122 to the user devices. Theunreadable portion may be, for a set of the plurality of sets of encodeddata slices, a sub-set of encoded data slices that include less than adecode threshold number of slices. For example, if the dispersed storageerror coding parameters include a pillar width of 16 and a decodethreshold of 10, then the sub-set of encoded data slices would be lessthan 10 (e.g., 8 or 9).

To facilitate the distribution of the sub-set of slices, the DSprocessing unit 16 identifies the targeted user devices 110, 12, 114,based on information from the content provider (e.g., a list ofsubscribers, of pre-paid orders, etc.) or information it derives (e.g.,likely to want the content, user devices in its domain, etc.). Havingidentified the targeted user devices, the DS processing unit sends writerequests regarding the sub-set of encoded data slices to the targeteduser devices in accordance with a distribution scheme (e.g., whatnetwork resources to use, time of day to transmit, how many slices totransmit for a given transmission, distribution duration—i.e., how muchtime to get the sub-set of slices to the targeted user devices, etc.).The write requests include the sub-set of encoded data slices and aninstruction to store them in the temporary slice memory 118.

When a user device desires the remainder of the content (e.g., releasedate occurs for a pre-paid content, a command from the user of thedevice, an automatic determination process, etc.), the user device sendsa request for the remaining encoded data slices of the set of encodeddata slices, which may be done for each of the sets separately, for thesets as a whole, or for groupings of sets. Upon receiving and validatingthe request, the DS processing unit sends the remaining encoded dataslices of the set, or a portion thereof, to the user device. The userdevice may then decode the received set of encoded data slices torecapture the data segment of the content.

When a user device does not desire the remainder of the content, itdeletes the sub-set of encoded data slices from it temporary slicememory. In this regard, the user device may delete the slices based on acommand from the DS processing unit 16, from a command embedded in theslices, or in response to a request as to what to do with the slices.

As a specific example, a wireless user device 110 is a targeted userdevice and has requested the remaining portion of the content. Therequest and subsequent transmission of encoded data slices may beconveyed via a base station 108, a wireless controller 102, a wirelesstransceiver 112, a distribution server 106, and/or a wireless router104. The wireless controller 102 controls the base station 108 such thatthe base station 108 converts slices 11 to wide-area signals 124 fortransmission to one or more wireless user devices 110. The base station108 may operate in accordance with one or more industry standards (e.g.,global system for mobile communications (GSM), code division multipleaccess (CDMA), etc.) and is operable to transmit and receive wide-areasignals. The wireless router 104 is operable to convert slices 11 intolocal area signals 126 for transmission to one or more wireless userdevices 110. The wireless router 104 may operate in accordance with oneor more industry standards (e.g., WIFI, Bluetooth, etc.) to transmit andreceive the local area signals 126.

The distribution server 106 distributes slices 11 (e.g., via a wirelineor wireless connection) to one or more of the wireless transceiver 112,the low tier user device 114, and the user device 12. The wirelesstransceiver 112 converts slices 11 into local area signals 126 fortransmission to one or more wireless user devices 110. The wirelesstransceiver 112 may operate in accordance with one or more industrystandards (e.g., WIFI, Bluetooth, etc.) to transmit and receive thelocal area signals 126.

In another example of operation, a wireless user device 100 that isoperably coupled to the base station 108 determines a user contentpreference and identifies target content in accordance with the usercontent preference. Based on the targeted content, the wireless userdevice 110 identifies public pillars (e.g., a sub-set of encoded dataslices) of the target content for a partial download and determines apartial downloading schedule (e.g., sending slices during off hours suchthat base station effectiveness is not compromised). For example, thewireless user device 110 sends a slice retrieval request to the DSNmemory 22, wherein the request includes a slice name associated with apublic pillar encoded data slice. Alternatively, or in addition to, theDS processing unit 16 determines the user content preference, identifiesthe target content, identifies the public pillars, determines thepartial downloading schedule, and facilitates partial downloading of thetarget content.

Continuing with this example, the wireless user device 110 receives thepublic pillar encoded slices, via the wide area signals 124, and storesthem in temporary slice memory 118. Next, the wireless user device 110determines whether the target content is desired. When the targetcontent is desired, the wireless user device 110 identifies one or morerequired private pillars of the desired target content (e.g., remainingencoded data slices of a set) and requests them. Upon receiving theprivate pillar encoded data slices, the wireless user devices storesthem in non-temporary slice memory 120 and moves the public pillarencoded data slices from the temporary slice memory 118 to thenon-temporary slice memory 120.

As yet another example of operation, the DS processing unit 16facilitates the downloading of content in an efficient. For instance,the DS processing unit selects network edge units for staging publicpillar encoded data slices, where the network edge units includes thewireless controller 102, the wireless router 104, the distributionserver 106, a user device 12, and/or a wireless user device 110. The DSprocessing unit 16 then identifies target content for partial downloadto the network edge units and identifies public pillars of the targetcontent. The DS processing unit further determines a partial downloadingschedule for sending the public pillar encoded data slices to thenetwork edge units in accordance with the downloading schedule.

Continuing with the preceding example, a user device 12 and/or awireless user device 110 identify target content for partialdownloading. The user device requests a download of the public pillarencoded data slices from a network edge unit and, upon receiving theslices, stores them in temporary slice memory 118. When the user devicedesires downloading the remainder of the content, it requests a downloadof the private pillar encoded data slices from the DSN memory 22 and/orfrom a network edge unit.

FIG. 7A is a schematic block diagram of another embodiment of acomputing system that includes a content provider 142, a computingdevice 130, and a plurality of potential accessing devices 131. Thecomputing device 130 may be implemented as a dispersed storage (DS)processing unit, a user device 12, and/or a DS unit. Each accessingdevice 131 may be implemented as a user device, a DS unit, and/oranother DS processing unit. For example, the computing device 130 is aDS processing unit commissioned to distribute multi-media content touser devices as the potential accessing devices 131. The computingdevice 130 includes a DS module 132 which includes an encode module 134,a partition module 136, a distribute module 138, and a completedistribution module 140.

The encode module 134 encodes a data segment of multi-media content 144using a dispersed storage error coding function to produce a set ofencoded data slices 146. The partition module 136 partitions the set ofencoded data slices 146 into a first sub-set of encoded data slices 148and a second sub-set of encoded data slices 150, wherein the firstsub-set of encoded data slices 148 include less than a decode thresholdnumber of encoded data slices. The encode module 134 and or partitionmodule may include a delete function with the encoded data slices 148which causes the user device to delete the first sub-set of encoded dataslices 148 when the accessing information 152 (e.g., request for theremainder of the content) is not received in a specified time frame.

The partition module 136 may partition the set of encoded data slices146 based on a pillar pattern, which includes less than the decodethreshold number of encoded data slices for the first sub-set. Thepartition module may select the pillar pattern based on the multi-mediacontent 144, the decode threshold number, a pillar width, a securityrequirement, a bandwidth availability indicator, and/or a cost ofbandwidth indicator. For example, the partition module 136 selects 9pillars when the decode threshold number is 10. As another example, thepartition module 136 selects 16 pillars when the decode threshold numberis 24 and a bandwidth availability indicator is below a bandwidththreshold (e.g., lower than average bandwidth availability to send thefirst sub-set of encoded data slices 148).

The distribute module 138 distributes the first sub-set of encoded dataslices 148 to the potential accessing devices 131. For example, thedistribute module 138 distributes the first sub-set of encoded dataslices 148 in advance of an available purchase date. As another example,the distribute module 138 identifies the potential accessing devices 131based on a likelihood of consumption (e.g., based on preferences such asa preferred genre, artists, movie type, music type etc. and/or aconsumption pattern) of the multi-media content 144 by the potentialaccessing device 131, receiving a content request (e.g., a purchaserequest) from the potential accessing device 131, receiving apre-purchase order for the multi-media content 144 from the potentialaccessing device 131, and polling the potential accessing device 131regarding accessing the multi-media content 144.

As yet another example, the distribute module 138 determines adistribution scheme and distributing the first sub-set of encoded dataslices 148 in accordance with the distribution scheme. For instance, thedistribution scheme may include using one or more connectivity routes tothe potential accessing devices, determining a system loading threshold,determining a time of day factor, and/or identifying intermediatedevices to facilitate the distribution of the first sub-set of encodeddata slices 148. For example, the distribute module 138 determines todistribute the first sub-set of encoded data slices 148 to the potentialaccessing device 131 by sending the first sub-set of encoded data slices148 to a base station first intermediate device at 3 PM and scheduling afinal distribution of the first subset of encoded data slices 148 fromthe base station first intermediate device to the potential accessingdevice 131 at 1 AM via a wide-area wireless network when availablebandwidth is high and cost is low.

The complete distribution module 140 sends at least one of the encodeddata slices 154 of the second sub-set of encoded data slices 150 to auser device in response to receiving accessing information 152 such thatthe device has a decode threshold number of encoded data slices. Theaccessing information 152 includes purchasing information to purchasethe multi-media content 144 and/or viewing information regarding viewingof the multi-media content 144. The purchasing information includes arequesting entity identifier, a potential accessing device identifier, amulti-media content identifier of the multi-media content 144, one ormore slice identifiers corresponding to previously received encoded dataslices of the first sub-sub of encoded data slices 148, and/ore-commerce transaction information (e.g., a credit card number). Theviewing information includes a watch now indicator, a watch laterindicator, a watch at any lowest cost possible indicator, and a watchand/or a specific time frame indicator.

FIG. 7B is a flowchart illustrating an example of distributingmulti-media content. The method begins at step 160 were a processingmodule (e.g., of a dispersed storage (DS) module) encodes a data segmentof multi-media content using a dispersed storage error coding functionto produce a set of encoded data slices. The encoding may furtherinclude embedding a delete function within a first sub-set of encodeddata slices, wherein the delete function is activated to delete thefirst sub-set of encoded data slices when accessing information is notreceived in a specified time frame.

The method continues at step 162 where the processing module partitionsthe set of encoded data slices into a first sub-set of encoded dataslices and a second sub-set of encoded data slices, wherein the firstsub-set of encoded data slices include less than a decode thresholdnumber of encoded data slices. The method continues at step 164 wherethe processing module distributes the first sub-set of encoded dataslices to a plurality of potential accessing devices, which may be donein advance of a release date, in accordance with a distribution scheme,etc. This step may further include identifying the potential accessingdevices, which may be done in a variety of ways. For example, apotential accessing device may be identified based on a likelihood ofconsumption of the multi-media content, by receiving a content requestfrom the potential accessing device, receiving a pre-purchase order forthe multi-media content from the potential accessing device, and/orpolling the potential accessing device regarding accessing themulti-media content. As another example, a potential accessing devicemay be identified based on a user content preference, a new contentlisting message, user desired content, a user content selection, usercontent selection history, a predictive algorithm, a message, a match toa demographic fit, and/or content already distributed.

When accessing information from a device of the potential accessingdevices is received, the method continues at step 166 where theprocessing module sends at least one of the encoded data slices of thesecond sub-set of encoded data slices to the device such that the devicehas the decode threshold number of encoded data slices. The accessinginformation includes purchasing information regarding purchasing themulti-media content and/or viewing information regarding viewing of themulti-media content. Note that the at least one of the encoded dataslices may be sent in accordance with a transmission protocol, whichincludes identifying encoded data slices of the set of encoded dataslices previously obtained by the device and selecting the at least oneof the encoded data slices from other slices of the set of slices suchthat the device has the decode threshold number of encoded data slices.

FIG. 8A is a flowchart illustrating another example of facilitatingpartial content downloading. The method begins at step 170 were aprocessing module (e.g., of a dispersed storage (DS) processing unit, auser device) identifies target content for a user device group. Thedetermination may be based on one or more of a user group contentpreference, a new content listing message, user group desired content, auser group content selection, user group content selection history, apredictive algorithm, a message, a match to a demographic fit, andcontent already sent. For example, the processing module identifies thetarget content when the target content includes music from an artistthat matches an artist entry of at least one user of the user groupcontent preference.

The method continues at step 172 where the processing module identifiesless than a decode threshold number of pillars corresponding to thetarget content for partial download. This may be done based on thetarget content, error coding parameters (e.g., a pillar width, a decodethreshold, a write threshold, a read threshold), an amount of data perpillar, a security requirement, a performance requirement,predetermination, a lookup, a pillar assignment for the user device, anda query. For example, the processing module identifies pillars 1-9 asthe public pillars corresponding to the target content when a decodethreshold is 10 and the security requirement indicates a withholdingpattern to withhold one pillar. The withholding pattern may indicate towithhold one or more pillars of a decode threshold number of pillars.

The method continues at step 174 where the processing module selects auser device of the user device group for storage of each public pillar.The selecting may be based on one or more of a user device availabilityindicator, a level of user device storage availability, and a userdevice security performance level indicator. For example, the processingmodule selects a first user device when the first user device isassociated with a user device storage availability that is greater thana level of user device storage availability of substantially all otheruser devices of the user device group.

The method continues at step 176 where the processing module determinesa partial downloading schedule for sending public pillar encoded dataslices corresponding to the public pillars. The schedule may include astart time, an end time, how much of the target content to partiallydownload, a minimum download rate, an average download rate, and amaximum download rate. The determining may be based on one or more of alocation of each user device of the user device group, an availabilityindicator of each user device of user device group, a local networkloading indicator associated with a network edge unit associated witheach user device of the user device group, a network loading indicator,historical network loading information, the target content, the size ofthe target content, a size of encoded data slices associated with thepublic pillars, user device availability of the selected user device, auser device type indicator (e.g., wireless and/or wireline), and asecurity requirement. For example, the processing module determines tostart the download to a wireless user device, with a maximum downloadrate of 10 kilobits per second, at 2 AM and complete the download by 3AM when the historical network loading information indicates that anetwork edge unit associated with the user device typically has moreavailable capacity in this time frame and the wireless user device isavailable.

The method continues at step 178 where the processing module facilitatespartial downloading of the target content by facilitating sending of thepublic pillar encoded data slices to at least the user device of theuser device group. The facilitating includes at least one of retrievingthe public pillar encoded data slices when the processing module isassociated with the user device and requesting sending of the publicpillar encoded data slices when the processing module is associated witha DS processing unit.

FIG. 8B is a flowchart illustrating an example of acquiring multi-mediacontent. The method begins with step 180 where a processing module(e.g., of a user device, a potential accessing device) receives publicpillar encoded data slices of target content. The receiving includesreceiving the public pillar encoded data slices from at least one of adispersed storage network (DSN) memory, a dispersed storage (DS)processing unit, a network edge unit, and another user device of a userdevice group. The method continues at step 182 where the processingmodule stores the public pillar encoded data slices in a temporary slicememory (e.g., of a slice memory of a user device). Alternatively, or inaddition to, the processing module may forward at least some of thepublic pillar encoded data slices to at least one other user device of auser device group when the other user device requires the public pillarencoded data slices.

The method continues at step 184 where the processing module determineswhether target content corresponding to the public pillar encoded dataslices are desired (e.g., does the user device want a partial downloadof the content). The determining may be based on one or more of a query,sending an indication of the target content (e.g., to a user interface),receiving a user selection input, receiving a user device groupselection, a predetermined selection, a target content list, anavailable memory indicator, a cost indicator, and a user contentpreference. The method loops back to step 180 when the processing moduledetermines that the target content is not desired. The method continuesto step 186 when the processing module determines that the targetcontent is desired.

The method continues at 186 where the processing module identifies oneor more required private pillars of the desired target content. Theidentification may be based on one or more of a query, a securityrequirement, a pillar assignment corresponding to the user device, apillar assignment corresponding to the user device group, privatepillars stored in the user device group, a lookup, error codingparameters, and a number of public pillars stored in the temporary slicememory. For example, the processing module determines pillars 8-11 asthe required private pillars when public pillars 1-7 are already storedin the temporary slice memory, pillars 8-9 are stored in at least oneother user device of the user device group, and a decode threshold ofthe error coding parameters is 11. As another example, the processingmodule determines pillars 15-16 as the required private pillars whenpillars 1-9 are stored in the temporary slice memory, a decode thresholdof the error coding parameters is 10, the read threshold is 11, and thepillar assignment corresponding to the user device group indicates toutilize pillars 15-16.

The method continues at step 188 where the processing module requestsencoded data slices corresponding to the one or more required privatepillars. The requesting includes sending at least one encoded data slicerequest to one or more of a dispersed storage (DS) processing unit,another user device of the user device group, and a DSN memory, whereinthe request includes at least one slice name associated with the one ormore required private pillars. The method continues at step 190 wherethe processing module receives private pillar encoded data slices of thedesired content. The method continues at step 192 where the processingmodule stores the private pillar encoded data slices in non-temporaryslice memory. The method continues at step 194 where the processingmodule moves the public pillar encoded data slices from the temporaryslice memory to the non-temporary slice memory. In addition, theprocessing module may retrieve at least a decode threshold number ofencoded data slices for each data segment of the desired target contentstored in the non-temporary slice memory, dispersed storage error decodethe at least decode threshold number of encoded data slices for eachdata segment to produce a plurality of data segments, and aggregate theplurality of data segments to reproduce the desired target content.

FIG. 9 is a flowchart illustrating an example of staging content fordownloading. The method begins at step 196 where a processing module(e.g., a dispersed storage (DS) processing unit) selects a plurality ofnetwork edge units for staging public pillar encoded data slices. Theselection may be based on one or more of a list of units, a unitrequest, a user device operably coupled to the unit, a geographic areaassociated with a unit, a content preference of a user device, aprevious partial download list, a new content listing message, a desiredcontent indicator of a user device, and a content selection history of auser device. For example, processing module selects a network edge unitthat is operably coupled to a user device that may require targetcontent downloading.

The method continues at step 198 where the processing module identifiestarget content for partial download to the plurality of network edgeunits. The identifying may be based on one or more of a unit request, auser device operably coupled to the unit, a content preference of a userdevice, a previous partial download list, a new content listing message,a desired content indicator of a user device, and a content selectionhistory of a user device. The method continues with step 172 of FIG. 8Awhere the processing module identifies public pillars corresponding tothe target content for partial download.

The method continues at step 202 where the processing module determinesa partial downloading schedule for sending public pillar encoded dataslices, corresponding to the public pillars, to each network edge unitof the plurality of network edge units. The schedule may include a starttime, an end time, how much of the target content to partially download,a minimum download rate, an average download rate, and a maximumdownload rate. The determining may be based on one or more of a locationof the network edge unit, an availability indicator of the network edgeunit, a network loading indicator associated with the network edge unit,and available network bandwidth associated with the network edge unit, alocation of a user device, an availability indicator of a user deviceassociated with the network edge unit, a network loading indicator,historical network loading information, the target content, the size ofthe target content, a size of encoded data slices associated with thepublic pillars, a user device type indicator (e.g., wireless and/orwireline), and a security requirement. For example, the processingmodule determines to start the download to a network edge unit, with amaximum download rate of 5 Mb per second, at 11:01 PM and complete thedownload by 11:15 PM when the historical network loading informationindicates that the network edge unit typically has more availablenetwork bandwidth in this time frame.

The method continues at step 204 where the processing module facilitatespartial downloading of the target content by facilitating sending of thepublic pillar encoded data slices to each network edge unit of theplurality of network edge units. The facilitating includes at least oneof retrieving of the public pillar encoded data slices when theprocessing module is associated with the network edge unit andrequesting sending of the public pillar encoded data slices when theprocessing module is associated with a DS processing unit.

FIG. 10A is a schematic block diagram of another embodiment of acomputing system that includes a dispersed storage (DS) processing unit16, a computing device 210, and at least one potential accessing device131. The computing device 210 may be implemented as at least one of apotential accessing device 131 and a user device. For example, the DSprocessing unit 16 distributes multi-media content to a plurality ofpotential accessing devices 131 that includes the potential accessingdevice 131 and the computing device 210. The computing device 210includes a DS module 212 and a memory 214. The memory 214 may beimplemented utilizing one or more memory devices including one or moreof a FLASH memory, random access memory, a magnetic disk drive, and anoptical disk drive. The DS module 212 includes a receive first slicesub-set module 216, a determine whether to request module 218, a sendaccessing information module 220, a receive slice module 222, and aremedy slice error module 224.

The receive first slice sub-set module 216, when operable within thecomputing device 210, causes the computing device 210 to receive a firstsub-set of encoded data slices 148, wherein a data segment ofmulti-media content was encoded using a dispersed storage error codingfunction to produce a set of encoded data slices, wherein the set ofencoded data slices is partitioned into the first sub-set of encodeddata slices 148 and a second sub-set of encoded data slices, and whereinthe first sub-set of encoded data slices 148 includes less than a decodethreshold number of encoded data slices. The receive first slice sub-setmodule 216 is operable to receive the first sub-set of encoded dataslices 148 by receiving a distribution of the first sub-set of encodeddata slices 148 to a plurality of potential accessing devices 131.

The receive first slice sub-set module 216 is further operable toreceive the first sub-set of encoded data slices 148 by at least one ofreceiving a message that includes the first sub-set of encoded dataslices 148 from at least one of the potential accessing device 131, adispersed storage (DS) processing unit, a user device, and anintermediate edge device of a dispersed storage network (DSN), receivingthe first sub-set of encoded data slices 148 in accordance with aregistered user program of a network (e.g., a wireless device affiliateswith a next site in a multisite wireless system), and sending a requestmessage for the first sub-set of encoded data slices 148. The sendingincludes identifying the multi-media content as likely to be acquired,generating the request, and outputting the request.

The receive first slice sub-set module 216 is further operable todetermine whether to forward one or more of the first sub-set of encodeddata slices 148 to a user device (e.g., another potential accessingdevice 131) and forward the one or more of the first sub-set of encodeddata slices 148 to the user device. The determining may be based on oneor more of receiving a request from the user device, determining that alikelihood level of acquisition of the multi-media content by the userdevice compares favorably with a likelihood level of acquisitionthreshold, and determining that a slice error exists of storage of thefirst sub-set of encoded data slices 148 within the user device.

The determine whether to request module 218, when operable within thecomputing device 210, causes the computing device 210 to determinewhether to request the second sub-set of encoded data slices. Thedetermine whether to request module 218 is operable to determine whetherto request the second sub-set of encoded data slices by determining whenthe multi-media content is available for purchase and when themulti-media content becomes available for purchase, indicating that thesecond sub-set of encoded data slices is to be requested.

The determine whether to request module 218 is further operable todetermine whether to request the second sub-set of encoded data slicesby at least one of determining whether a storage time frame of the firstsub-set of encoded data slices has expired and, when the storage timeframe has expired, indicating the that the second sub-set of encodeddata slices is not going to be requested (e.g., acquisition unlikelywhen too much time has elapsed), and determining a probability that thesecond sub-set of encoded data slices will be requested and, when theprobability is likely that the second sub-set of encoded data sliceswill be requested, indicating that the second sub-set of encoded dataslices is to be requested. For example, the probability that the secondsub-set of encoded data slices will be requested is certain whenreceiving a user input selecting the multi-media content for purchaseand/or viewing. As another example, the probability that the secondsub-set of encoded data slices will be requested is high when anattribute of the multi-media content substantially matches a desiredattribute (e.g., content is on a desired playlist, content matches userpreferences such as artist, genre, topic, type, etc).

The determine whether to request module 218 is further operable toadjust the storage time frame. For example, the storage time frame isshortened when memory 214 has less available storage capacity. Thedetermine whether to request module 218 is further operable totemporarily store the first sub-set of encoded data slices (e.g., in thememory 214) prior to sending the accessing information 152 and when thesecond sub-set of encoded data slices is not to be requested, facilitatedeletion of the first sub-set of encoded data slices 148 (e.g., deletingfrom the memory 214).

The send accessing information module 220, when operable within thecomputing device 210, causes the computing device 210 to, when thesecond sub-set of encoded data slices is to be requested, send accessinginformation 152 regarding the second sub-set of encoded data slices. Forexample, the send accessing information module 220 identifies at leastone of the encoded data slices 154 of the second sub-set of encoded dataslices such that when combined with the first sub-set of encoded dataslices 148 provides a decode threshold number of encoded data slices,generates the accessing information 152 to include the identity of theat least one of encoded data slices 154, and outputs the accessinginformation 152. The outputting includes sending the accessinginformation 152 to at least one of the DS processing unit 16 and thepotential accessing device 131.

The receive slice module 222, when operable within the computing device210, causes the computing device 210 to receive, in response to theaccessing information 152, at least one of the encoded data slices 154of the second sub-set of encoded data slices such that the decodethreshold number of encoded data slices have been received. Thereceiving includes receiving the at least one of the encoded data slices154 from at least one of the DS processing unit 16 and the potentialaccessing device 131.

The remedy slice error module 224, when operable within the computingdevice 210, causes the computing device 210 to determine whether one ormore of the first sub-set of encoded data slices 148 has a slice error(e.g., detecting a missing slice and/or detecting unfavorable sliceintegrity), when the slice error exists identify one or more slice namescorresponding to the one or more of the first sub-set of encoded dataslices having the slice error and request the one or more of the firstsub-set of encoded data slices having the slice error from one or moredevices of a user group based on the one or more slice names. Forexample, the remedy slice error module 224 detects a slice error, sendsa slice request to the potential accessing device 131, receives areplacement slice from the potential accessing device 131, and storesthe replacement slice in the memory 214.

FIG. 10B is a flowchart illustrating an example of acquiring multi-mediacontent. The method begins at step 230 were a processing module (e.g.,of a dispersed storage (DS) module of a potential accessing device)receives a first sub-set of encoded data slices, wherein a data segmentof multi-media content was encoded using a dispersed storage errorcoding function to produce a set of encoded data slices, wherein the setof encoded data slices is partitioned into the first sub-set of encodeddata slices and a second sub-set of encoded data slices, and wherein thefirst sub-set of encoded data slices include less than a decodethreshold number of encoded data slices. The receiving the first sub-setof encoded data slices includes receiving a distribution of the firstsub-set of encoded data slices to a plurality of potential accessingdevices. The receiving the first sub-set of encoded data slices furtherincludes at least one of receiving a message that includes the firstsub-set of encoded data slices from at least one of a dispersed storage(DS) processing unit, a user device, another potential accessing device,and an intermediate edge device of a dispersed storage network (DSN).The receiving the first sub-set of encoded data slices further includesreceiving the first sub-set of encoded data slices in accordance with aregistered user program of a network (e.g., site affiliationregistration, system affiliation registration, system access) andsending a request message for the first sub-set of encoded data slices.

The method continues at step 232 where the processing module temporarilystores the first sub-set of encoded data slices prior to sendingaccessing information with regards to the second sub-set of encoded dataslices. The method continues at step 234 where the processing moduledetermines whether to forward one or more of the first sub-set ofencoded data slices to a user device (e.g., another potential accessingdevice of a group of accessing devices that includes the potentialaccessing device). The determination may be based on one or more ofreceiving a request, a predetermination, and determining that the userdevice is likely to acquire the multi-media content. The method branchesto step 238 when the processing module determines not to forward the oneor more of the first sub-set of encoded data slices to the user device.The method continues to step 236 when the processing module determinesto forward the one or more of the first sub-set of encoded data slicesto the user device. The method continues at step 236 where theprocessing module forwards the one or more of the first sub-set ofencoded data slices to the user device when forwarding. The methodbranches to step 238.

The method continues at step 238 where the processing module determineswhether one or more of the first sub-set of encoded data slices has aslice error. The method branches to step 244 when the processing moduledetermines that there is no slice error. The method continues to step240 when the processing module determines that there is a slice error.When the slice error exists, the method continues at step 240 where theprocessing module identifies one or more slice names corresponding tothe one or more of the first sub-set of encoded data slices having theslice error (e.g., from an unfavorable comparison of list responsesand/or list digest responses). The method continues at step 242 wherethe processing module requests the one or more of the first sub-set ofencoded data slices having the slice error from one or more devices of auser group based on the one or more slice names. For example, theprocessing module generates a read slice request that includes the oneor more slice names, identifies the one or more user devices of the usergroup (e.g., a group of affiliated potential accessing devices), outputsthe read slice request to the one or more user devices, and receives aread slice response that includes replacement slices for the one or moreof the first sub-set of encoded data slices have in a slice error.

The method continues at step 244 where the processing module determineswhether to request the second sub-set of encoded data slices. Thedetermining whether to request the second sub-set of encoded data slicesincludes determining when the multi-media content is available forpurchase and when the multi-media content becomes available forpurchase, indicating that the second sub-set of encoded data slices isto be requested. The determining whether to request the second sub-setof encoded data slices further includes at least one of determiningwhether a storage time frame of the first sub-set of encoded data sliceshas expired and, when the storage time frame has expired, indicating thethat the second sub-set of encoded data slices is not going to berequested and determining a probability that the second sub-set ofencoded data slices will be requested and, when the probability islikely that the second sub-set of encoded data slices will be requested,indicating that the second sub-set of encoded data slices is to berequested. The method branches to step 248 when the processing moduledetermines the request the second sub-set of encoded data slices. Themethod continues to step 246 when the processing module determines notto request the second sub-set of encoded data slices. When the secondsub-set of encoded data slices is not to be requested, the methodcontinues at step 246 where the processing module facilitates deletionof the first sub-set of encoded data slices.

When the second sub-set of encoded data slices is to be requested, themethod continues at step 248 where the processing module sends accessinginformation regarding the second sub-set of encoded data slices. Thesending includes generating the accessing information and outputting theaccessing information to at least one of a DS processing unit, a userdevice, and another potential accessing device. The method continues atstep 250 with a processing module receives, in response to the accessinginformation, at least one of the encoded data slices of the secondsub-set of encoded data slices such that the decode threshold number ofencoded data slices have been received. The receiving may furtherinclude decoding the decode threshold number of encoded data slices toreproduce the data segment of multi-media content. The method may repeatsuch that a plurality of data segments are reproduced enablingreproduction of the multi-media content for storage and/or consumption.

FIG. 11 is a flowchart illustrating an example of maintainingtemporarily stored encode data slices, which include similar steps toFIG. 8A. The method begins steps 180 and 182 of FIG. 8A where aprocessing module (e.g., of a user device) receives public pillarencoded data slices of target content and stores the public pillarencoded data slices in a temporary slice memory. The method continues atstep 256 where the processing module determines whether to delete atleast some of the public pillar encoded data slices from the temporaryslice memory. The determination may be based on one or more of anestimation of a likelihood of a full download being desired, alikelihood threshold, previous user selection, a user preference, apredetermination, a target content list, a slice age indicator, an agethreshold, a memory capacity indicator, and a memory threshold. Forexample, the processing module determines to delete the at least some ofthe public pillar encoded data slices when the estimation of thelikelihood of the full download being desired is less than thelikelihood threshold. As another example, the processing moduledetermines to delete the at least some of the public pillar encoded dataslices when a user preference compares unfavorably to the targetcontent. As another example, the processing module determines to deletethe at least some of the public pillar encoded data slices when theslice age indicator is greater than the age threshold. As yet anotherexample, the processing module determines to not delete the at leastsome of the public pillar encoded data slices when the slice ageindicator is greater than the age threshold and the memory capacityindicator is greater than a memory threshold.

The method branches to step 260 when the processing module determinesnot to delete the at least some of the public pillar encoded dataslices. The method continues to step 258 when the processing moduledetermines to delete the at least some of the public pillar encoded dataslices. The method continues at step 258 where the processing moduledeletes the at least some of the public pillar encoded data slices fromthe temporary slice memory. The deleting may include determining howmany pillars to delete based on one or more of the slice age indicator,the memory capacity indicator, a slice size indicator, a number ofpillars to delete associated with a time frame indicator, and errorcoding parameters. For example, the processing module deletes one pillarof encoded public pillar encoded data slices when the number of pillarsto delete associated with the time frame indicator indicates to deleteone pillar at a first time period. As another example, the processingmodule deletes all pillars of the encoded public pillar encoded dataslices when the number of pillars to delete associated with the timeframe indicator indicates to delete all pillars at a maximum timeperiod.

The method continues at step 260 where the processing module determineswhether a slice error exists of a plurality of public pillar encodeddata slices stored in the temporary slice memory. The slice errorincludes at least one of a missing slice, a corporate slice (e.g.,detected by an unfavorable comparison of a calculated integrity checkvalue to a retrieved integrity check value of an encoded data slice),and a number of stored slices corresponding to allowed pillars is lessthan a number of allowed pillars. The determining may be based on one ormore of a query, an integrity test, an error message, an allowed numberof pillars, a pillar assignment, and a comparison of a slice name listto a second slice name list. For example, processing module determines aslice error exists when 7 public pillar encoded data slices of a set ofencoded data slices are stored in the temporary slice memory and thepillar assignment includes allowing a storage of 9 public pillar encodeddata slices of a set of encoded data slices. In such an example, twopublic pillar encoded data slices may have been previously deleted. Themethod repeats back to step 180 when the processing module determinesthat the slice error does not exist. The method continues to step 262when the processing module determines that the slice error exists.

The method continues at step 262 where the processing module retrieves areplacement encode data slice corresponding to the slice error. Theretrieving includes retrieving the encoded data slice from at least oneof a dispersed storage network (DSN) memory, an edge network unit, andfrom another user device. The replacement encoded data slice maycorrespond to a same pillar number associated with the slice error or adifferent pillar number (e.g., that same set of slices) when such adifferent pillar number is included in the pillar assignment. The methodcontinues at step 264 where the processing module stores the replacementencoded data slice in the temporary slice memory. The method repeatsback to step 180.

FIG. 12A is a schematic block diagram of an embodiment of a wirelessuser device 266 that includes a dispersed storage (DS) processing 34, aslice memory 270 (e.g., including at least one of a temporary slicememory and a non-temporary slice memory), and a plurality of wirelesstransceivers 268. Each wireless transceiver 268 transmits and receiveswireless signals 272 in accordance with one or more industry standards(e.g., global system for mobile communications (GSM), code divisionmultiple access (CDMA) etc.

The wireless user device 266 establishes one or more wirelessconnections (e.g., sending and receiving wireless signals 272 with atleast one other wireless device) to form a communications path toreceive encoded data slices 11 for storage in the slice memory 270. Theother wireless device includes one or more of another wireless userdevice 266, a base station, a wireless router, and a wirelesstransceiver. The communications path may include one or more wirelessconnections. For example, a 100 kb per second communications path mayinclude a 75 kb per second wireless connection on a first wirelesstransceiver 268 and a 25 kb per second wireless connection on a secondwireless transceiver 268. The encoded data slices 11 may include publicpillar encoded data slices 11 and private pillar encoded data slices 11.The storage of encoded data slices 11 includes storing public pillarencoded data slices 11 in the temporary memory of the slice memory 270and storing private pillar encoded data slices 11 in the non-temporarymemory of the slice memory 270.

The wireless user device 266 may receive the public pillar encoded dataslices 11 and the private pillar encoded data slices 11 from differentsources utilizing different wireless signals 272. For example, thewireless user device 266 receives public pillar encoded data slices 11via the first wireless transceiver 268 and private pillar encoded dataslices 11 via the second wireless transceiver 268. A method of operationof the wireless user device 266 is described in greater detail withreference to FIG. 12B.

FIG. 12B is a flowchart illustrating an example of communicating encodeddata slices via a wireless connection. The method begins at step 274where a processing module (e.g., of a wireless user device) establishesa first wireless connection. The establishing includes receiving and/ortransmitting wireless signals with at least one other wireless devicesuch that at least a portion of a communications path is establishedbetween the processing module and the other wireless device.

The method continues at step 276 where the processing module determinesfirst dispersal parameters based on the first wireless connection. Thedispersal parameters of the first dispersal parameters includes at leastone of a pillar width, a write threshold, a read threshold, a decodethreshold, and an error coding matrix. The determining may be based onwireless signal parameters of the first wireless connection includingone or more of an error rate, an error rate threshold, a communicationspath bandwidth, a bandwidth threshold, an information transfer latency,a latency threshold, a communications path speed (e.g., bits persecond), and a speed threshold. For example, the processing moduledetermines a pillar width and decode threshold with an above averagedifference when the error rate is greater than the error threshold. Asanother example, the processing module determines a lower than averagepillar width when the communications path speed is less than the speedthreshold.

The method continues at step 278 where the processing module receives afirst plurality of sets of encoded data slices of target content via thefirst wireless connection, wherein the first plurality of sets ofencoded data slices are encoded utilizing the first dispersalparameters. The receiving may include sending the first dispersalparameters to another wireless device associated with the first wirelessconnection for utilization in encoding the slices.

The method continues at step 280 where the processing module establishesa second wireless connection. For example, the processing moduleestablishes a new wireless connection as the second wireless connection.As another example, the processing module establishes the first wirelessconnection as the second wireless connection. The method continues atstep 282 where the processing module determines second dispersalparameters based on the second wireless connection. The determining maybe based on wireless signal parameters of the second wireless connectionincluding one or more of an error rate, an error rate threshold, acommunications path bandwidth, a bandwidth threshold, an informationtransfer latency, a latency threshold, a communications path speed(e.g., bits per second), and a speed threshold.

The method continues at step 284 where the processing module receives asecond plurality of sets of encoded data slices of target content viathe second wireless connection, wherein the second plurality of sets ofencoded data slices are encoded utilizing the second dispersalparameters. The receiving may include sending the second dispersalparameters to another wireless device associated with the secondwireless connection for utilization in encoding the slices.

The method continues at step 286 where the processing module saves thefirst and second plurality of sets of encoded data slices as targetcontent slices. The saving includes storing the first and secondplurality of sets of encoded data slices in a temporary slice memory. Inaddition, the processing module may dispersed storage error decode theplurality of sets of encoded data slices utilizing the first and seconddispersal parameters to reproduce the target content.

FIG. 13 is a schematic block diagram of another embodiment of acomputing system that includes a plurality of data collection dispersedstorage (DS) processing units 290, a send node 292, a receive node 294,a data storage node 296, a plurality of sensor nodes 298, a network 24,a dispersed storage network (DSN) memory 22, and a data analysis DSprocessing unit 300. The DSN memory 22 includes a plurality of DS units36. The send node 292, receive node 294, data storage node 296, andplurality of sensor nodes 298 may include a portable or fixedcommunications and/or computing device and may be implemented utilizingone or more of a computing core, a wireless interface, a wirelineinterface, a user interface, a memory unit, a disk drive, and a memorydevice. The sensor node 298 may include one or more sensors implementedto sense one or more of environmental conditions, motion, radarreflections, communications traffic levels, recognize images, recognizepatterns, recognize speech, and recognize keyword detections.

Each data collection DS processing unit 290 of the plurality of datacollection DS processing units 290 is operable to select data inaccordance with a data selection method (e.g., based on a data type, adata priority indicator, a data bandwidth, available memory, availablebandwidth to the DSN memory), receive data for storage (e.g.,communicated data, stored data, such a data), establish dispersedstorage error coding function parameters (e.g., based on a data type, adata priority indicator, a data bandwidth, available memory, availablebandwidth to the DSN memory), dispersed storage error encode the datautilizing a dispersed storage error coding function in accordance withthe dispersed storage error coding function parameters to produce aplurality of slices 11, establish a priority indicator and a timestampassociated with the data (e.g., time & date of arrival), and send theslices 11, the priority indicator, and the timestamp to the DSN memory22 for storage therein. The data includes at least one of communicateddata 302 transmitted from the send node 292 to at least one receive node294, stored data 304 received from the data storage node 296, and sensordata 306 from one or more of the plurality of sensor nodes 298. Thecommunicated data 302 includes at least one of wireline communicationsand wireless communications to communicate data including multimedia,video, audio, and data files. The stored data 304 includes one or moreof multimedia, video, audio, and data files. The sensor data 306includes one or more of sensed patterns, sensed variable levels, and rawsensor data.

The priority indicator may be utilized to prioritize a timeframe of dataretention of the data. For example, a high priority level of thepriority indicator for data indicates that the data shall be retainedfor a longer than average timeframe and perhaps indefinitely. As anotherexample, a low priority level of the priority indicator for dataindicates that the data shall be retained for a minimum and shorter thanaverage timeframe. The priority indicator may be associated with dataand/or each slice of the plurality of slices 11 of the data. Forexample, a slice with a high priority level that is associated with dataof a low priority level shall be retained for a longer than averagetimeframe. As another example, a slice with a low priority level that isassociated with data of a high priority level shall be retained for alonger than average timeframe. As yet another example, a slice with alow priority level that is associated with data of a low priority levelshall be retained for a shorter than average timeframe.

A DSN directory may include a pathname field, a data priority indicatorfield, and a source name field, wherein the data priority indicatorfield includes a data priority indicator entry signifying a prioritylevel associated with data of a pathname entry in the pathname fieldstored in the DSN memory utilizing a source name address entry of thesource name field. A slice name field may include a slice priorityindicator field, wherein an associated slice priority indicator entrysignifies a priority level associated with a slice of a correspondingslice name. The slice name of the slice name field may be communicatedbetween the data collection DS processing unit 290, the DSN memory 22,and the data analysis DS processing unit 300.

The DSN memory 22 may include a significant number of DS units 36 tocreate a storage system of massive scale (e.g., tens of thousands ofexabytes). Each DS unit 36 of the DSN memory 22 is operable to receive(e.g., from a data collection DS processing unit 290) one or more of aslice of the plurality of slices 11, a slice name of the slice, a datapriority indicator (e.g., for data associated with the slice), a slicepriority indicator, and a timestamp; store one or more of the slice, theslice name, the data priority indicator, the slice priority indicator,and the timestamp in a local memory of the DS unit 36; delete the slicefrom the local memory based on a slice deletion method; rebuild theslice when a slice error is detected associated with the slice; andoutputting one or more of the slice, the slice name, the data priorityindicator, the slice priority indicator, and the timestamp in responseto a retrieval request (e.g., from the data analysis DS processingunit). A method of operation to capture data slices 11, store the slices11, delete slices 11, and rebuild slices 11 of the system is discussedin greater detail with reference to FIGS. 14A-17B.

The data analysis DS processing unit 300 is operable to retrieve (e.g.,from the DSN memory 22) one or more of slices 11 of the plurality ofslices 11, the slice name of the slice, the data priority indicator, theslice priority indicator, and the timestamp; dispersed storage errordecode the slices 11 to reproduce data in accordance with error codingdispersal parameters; facilitate analysis of the data to produce a dataanalysis; store the data analysis in the DSN memory 22; and establish amodified data priority indicator and/or a modified slice priorityindicator based on the data analysis. The data analysis DS processingunit 300 is further operable to store the modified data priorityindicator and/or the modified slice priority indicator in the DSN memory22; facilitate deletion of a slice of the plurality slices 11 from theDSN memory based on the slice deletion method; rebuild a slice when aslice error is detected associated with the slice; and output one ormore of the data, the data analysis, the plurality slices 11, the slicename, the data priority indicator, the modified data priority indicator,the slice priority indicator, the modified slice priority indicator, andthe timestamp in response to a retrieval request (e.g., from a userdevice associated with the data analysis DS processing unit).Alternatively, the data collection DS processing unit 290 may beutilized to implement the data analysis DS processing unit 300. A methodof operation of the data analysis DS processing unit 300 is discussed ingreater detail with reference to FIGS. 14A-17B.

In an example of operation, a text file is received as communicated data3 to 2 by a data collection DS processing unit 290. The data collectionDS processing unit 290 establishes dispersed storage error codingfunction parameters to include a pillar width of 16 and a decodethreshold of 10 based on a lookup of default error coding dispersalparameters for a text file. The data collection DS processing unit 290dispersed storage error encodes the text file in accordance with thedispersed storage error coding function parameters to produce aplurality of text slices 11. The data collection DS processing unit 290generates a plurality of slice names corresponding to the plurality oftext slices 11. The data collection DS processing unit 290 establishes apriority indicator level of 5 based on a lookup for a default prioritylevel for a text file and establishes a timestamp of a current systemtime and date. The data collection DS processing unit 290 sends theplurality of text slices 11, the plurality of slice names, the priorityindicator level of 5, and the timestamp to the DSN memory 22 for storagetherein.

In the example of operation continued, a DS unit 36 of the plurality ofDS units 36 determines to delete a text slice 11 of the plurality oftext slices 11, wherein the text slice 11 is associated with a slicepriority level of 2 and a timestamp that compares unfavorably to acurrent timestamp (e.g., an amount of elapsed time since the timestampis greater than a time threshold). Next, the DS unit 36 deletes the textslice 11. The deletion lowers a number of retrievable pillar slices byone but may not lower the number below the decode threshold of 10.

In the example of operation continued, the data analysis DS processingunit 300 retrieves (e.g., from the DSN memory 22) a decode thresholdnumber of text slices of each data segment of the plurality of textslices, the data priority indicator of 5, and the timestamp. The dataanalysis DS processing unit 300 dispersed storage error decodes thedecode threshold number of text slices 11 of each data segment of theplurality of text slices 11 to reproduce the text file in accordancewith dispersed storage error coding function parameters. The dataanalysis DS processing unit 300 facilitates analysis of the text file toproduce a data analysis. The data analysis DS processing unitestablishes a modified data priority indicator of 8 based on the dataanalysis and stores the modified data priority indicator of 8 in the DSNmemory 22.

FIG. 14A is a schematic block diagram of another embodiment of acomputing system that includes a computing device 310 and a dispersedstorage network (DSN) memory 22. The computing device 310 may beimplemented as at least one of a data collection dispersed storage (DS)processing unit, a data analysis DS processing unit, a DS processingunit, a DS unit, and a user device. The computing device 310 includes aDS module 312. The DS module 312 includes a monitor storage module 314,a determine analysis priority module 316, a delete module 318, and ananalyze module 320.

The monitor storage module 314, when operable within the computingdevice 310, causes the computing device 310 to monitor storage of data322, wherein the data 322 is encoded using a dispersed storage errorcoding function to produce a plurality of sets of encoded data slices324 and is stored as the plurality of sets of encoded data slices 324 inthe DSN memory 22. Alternatively, the monitor storage module 314 isfurther operable to encode the data utilizing the dispersed storageerror coding function to produce the plurality of sets of encoded dataslices 324 and store the plurality of sets of encoded data slices 324 inthe DSN memory 22.

The monitor storage module 314 is further operable to determine a datacharacterization of the data 322, wherein the data characterizationincludes at least one of a time factor (e.g., when ingested, whenstored), a data source factor (e.g., a sending entity), a data contentfactor (e.g., a data type indicator, a data identifier (ID)), and a datalocation origination factor (e.g., a sourcing entity). The determineanalysis priority module 316, when operable within the computing device310, causes the computing device 310 to determine analysis priority 326of the data 322 in accordance with an analysis prioritization protocol.The analysis priority protocol includes at least one of a time basedscaling factor, a data source based scaling factor, a data content basedscaling factor, and a data location origination based scaling factor,wherein the analysis priority protocol is a function of the scalingfactors.

The monitor storage module 314 is further operable to determine apriority level of the data 322 based on the data characterization andthe analysis priority protocol and select parameters for the dispersedstorage error coding function based on the priority level. For example,the monitor storage module 314 selects a decode threshold number of 3and a pillar width of 4 when the priority level indicates a higher thanaverage priority level (e.g., few slices to delete since data analysisis expected soon after storage). As another example, the monitor storagemodule 314 selects a decode threshold number of 20 and a pillar width of32 when the priority level indicates a lower than average priority level(e.g., more slices to delete as time goes on). The determining of thepriority level of the data 322 may further include generating an initialpriority level and storing the initial priority level. The initialpriority level may include one or more of the data characterization, theanalysis priority protocol, the parameters for the dispersed storageerror coding function, and a priority level number.

The delete module 318, when operable within the computing device 310,causes the computing device 310 to, when the analysis priority 326 ofthe data 322 compares unfavorably to a first priority threshold, issue acommand 328 to delete an encoded data slice from each set of at leastsome of the plurality of sets of encoded data slices 324. The deletemodule 318 is further operable to, when the analysis priority 326 of thedata 322 compares unfavorably to a second priority threshold, issue asecond command to delete the encoded data slice and at least one otherencoded data slice from each set of the at least some of the pluralityof sets of encoded data slices 324.

The delete module 318 is further operable to determine, in accordancewith the analysis prioritization protocol, that analysis of the data isno longer desired and when the analysis of the data is no longerdesired, issue another command to delete the plurality of sets ofencoded data slices 324. The delete module 318 is further operable to,when the analysis priority of the data 322 compares unfavorably to thefirst priority threshold, issue a no-rebuilding command 330 regardingthe encoded data slices from each set of the at least some of theplurality of sets of encoded data slices 324 (e.g., indicating that theone or more encoded data slices do not require rebuilding) and updateparameters of the dispersed storage error coding function to reflect thedeletion of encoded data slices from each set of the at least some ofthe plurality of sets of encoded data slices 324 (e.g., lower a pillarwidth in a registry for an associated vault and object number).

The analyze module 320, when operable within the computing device 310,causes the computing device 310 to analyze the data 322. The deletemodule 318 is further operable to determine, based on the analyzing thedata, that the data 322 can be deleted and when the data 322 can bedeleted, issue yet another command to delete the plurality of sets ofencoded data slices 324.

FIG. 14B is a flowchart illustrating an example of deleting data storedin a dispersed storage network (DSN). The method begins at step 340where a processing module (e.g., of a data analysis dispersed storage(DS) processing unit) determines a data characterization of data,wherein the data characterization includes at least one of a timefactor, a data source factor, a data content factor, and a data locationorigination factor.

The method continues at step 342 where the processing module determinesa priority level of the data based on the data characterization and ananalysis priority protocol. The analysis priority protocol includes oneor more of a time based scaling factor, a data source based scalingfactor, a data content based scaling factor, and a data locationorigination based scaling factor, wherein the analysis priority protocolis a function of the scaling factors. The method continues at step 344where the processing module selects parameters for the dispersed storageerror coding function based on the priority level.

The method continues at step 346 for the processing module monitorsstorage of data, wherein the data is encoded using a dispersed storageerror coding function to produce a plurality of sets of encoded dataslices and is stored as the plurality of sets of encoded data slices.The method continues at step 348 where the processing module determinesanalysis priority of the data in accordance with the analysisprioritization protocol. When the analysis priority of the data comparesunfavorably to a first priority threshold, the method continues at step350 where the processing module issues a command to delete an encodeddata slice from each set of at least some of the plurality of sets ofencoded data slices. For example, the processing module issues a commandto delete one encoded data slice from each set of the plurality of setsof encoded data slices when the analysis priority is less than the firstpriority threshold and at least a decode threshold number of encodeddata slices will remain in each set of the plurality of sets of encodeddata slices after deleting the one encoded data slice.

The method continues at step 352 where the processing module issues ano-rebuilding command regarding the encoded data slices from each set ofthe at least some of the plurality of sets of encoded data slices. Forexample, processing module sends the no-rebuilding command to a DSNmemory associated with storage of the plurality of sets of encoded dataslices. As another example, the processing module sends theno-rebuilding command to one or more DS processing units associated withthe DSN memory. As yet another example, the processing module sends theno-rebuilding command to a storage integrity processing unit associatedwith the DSN.

A method continues at step 354 where the processing module updatesparameters of the dispersed storage error coding function to reflect thedeletion of encoded data slices from each set of the at least some ofthe plurality of sets of encoded data slices. For example, theprocessing module updates a registry associated with the data toindicate a lowered pillar width number. When the analysis priority ofthe data compares unfavorably to a second priority threshold, the methodcontinues at step 356 where the processing module issues another commandto delete the encoded data slice and at least one other encoded dataslice from each set of the at least some of the plurality of sets ofencoded data slices.

The method continues at step 358 where the processing module determines,in accordance with the analysis prioritization protocol, that analysisof the data is no longer desired. For example, the processing moduleindicates that analysis of the data is no longer desired when too muchtime has expired since storage of the data without analysis. As anotherexample, the processing module indicates that analysis of the data is nolonger required when receiving a message that the data is no longer ofinterest. When the analysis of the data is no longer desired, the methodcontinues at step 360 where the processing module issues a yet anothercommand to delete the plurality of sets of encoded data slices.

The method continues at step 362 where the processing module analyzesthe data. The analyzing includes one or more of searching the data tomatch a search term, counting a number of occurrences of a characterstring, identifying a correlation of a source of the data to a previousknown data source, identifying a data pattern, determining whether thedata may be deleted, and identifying a data element of interest based ona list of previously identified data elements of interest. The methodcontinues at step 364 where the processing module determines, based onthe analyzing the data, whether the data can be deleted. For example,the processing module determines that the data can be deleted whensearching the data to match the search term revealed no matches. Whenthe data can be deleted, the method continues at step 366 where theprocessing module issues a still further command to delete the pluralityof sets of encoded data slices.

FIG. 15 is a flowchart illustrating an example of deleting data storedin a dispersed storage network (DSN). The method begins at step 370where a processing module (e.g., a dispersed storage (DS) processingunit, a DS unit) obtains a slice priority level indicator of an encodeddata slice. The obtaining includes at least one of retrieving thepriority level indicator from a DS unit that stores the encoded dataslice, retrieving the priority level indicator from a DSN directory, andreceiving the priority level indicator. The method continues at step 372where the processing module obtains a timestamp associated with theencoded data slice. The obtaining includes at least one of retrievingthe timestamp from the DS unit that stores the encoded data slice,retrieving the timestamp from a DSN directory, and receiving thetimestamp.

The method continues at step 374 where the processing module determineswhether to delete the encoded data slice based on at least one of theslice priority level indicator and the timestamp. For example, theprocessing module determines to delete the encoded data slice when anamount of elapsed time since the timestamp is greater than a timethreshold corresponding to the slice priority level. For instance, theprocessing module determines to delete the encoded data slice when 30days has elapsed since the timestamp, the time threshold is 30 days, andthe slice priority level is 3. As another instance, the processingmodule determines not to delete the encoded data slice when 45 days haselapsed since the timestamp, a time threshold is infinite, and the slicepriority level is 10. As yet another instance, the processing moduledetermines to delete the encoded data slice when zero days has elapsedsince the timestamp, a time threshold is 0, and the slice priority levelis 0.

The method repeats back to step 370 when the processing moduledetermines not to delete the encoded data slice. The method continues tostep 376 when the processing module determines to delete the encodeddata slice. The method continues at step 376 where the processing modulefacilitates deletion of encoded data slice. The facilitating includes atleast one of sending a delete request message to the DS unit associatedwith encoded data slice that includes a slice name of encoded data slicewhen the processing module is associated with a DS processing unit anddeleting the encoded data slice when the processing module is associatedwith the DS unit. The method repeats back to step 370.

FIG. 16 is a flowchart illustrating an example of rebuilding data storedin a dispersed storage network (DSN), which includes similar steps toFIG. 15. The method begins at step 378 where a processing module (e.g.,a dispersed storage (DS) processing unit, a DS unit) detects a sliceerror of an encoded data slice. The detecting includes at least one ofdetecting a missing slice, detecting a slice that fails an integritycheck, and setting an error flag corresponding to a slice name of theencoded data slice. The method continues with steps 370-372 of FIG. 15where the processing module obtains a slice priority level indicator ofthe encoded data slice and obtains a timestamp associated with theencoded data slice.

The method continues at step 384 where the processing module determineswhether to rebuild the encoded data slice based on the slice prioritylevel indicator and the timestamp. For example, the processing moduledetermines to rebuild the encoded data slice when an amount of elapsedtime since the timestamp is less than a time threshold corresponding tothe slice priority level. For instance, the processing module determinesto rebuild the encoded data slice when 20 days has elapsed since thetimestamp, the time threshold is 30 days, and the slice priority levelis 3. As another instance, the processing module determines not torebuild the encoded data slice when 45 days has elapsed since thetimestamp, the time threshold is 30, and the slice priority level is 9.As yet another instance, the processing module determines to rebuild theencoded data slice when 1 day has elapsed since the timestamp, a timethreshold is 10, and the slice priority level is 1. The method repeatsback to step 378 when the processing module determines not to rebuildthe encoded data slice. The method continues to step 386 when theprocessing module determines to rebuild the encoded data slice.

The method continues at step 386 where the processing module facilitatesrebuilding of the encoded data slice. The facilitating includes at leastone of sending a rebuild request message to the DS unit associated withencoded data slice that includes a slice name of encoded data slice whenthe processing module is associated with a DS processing unit andrebuilding the encoded data slice when the processing module isassociated with the DS unit. The rebuilding includes at least one ofretrieving a decode threshold number of encoded data slices associatedwith the encoded data slice, decoding the least the decode thresholdnumber of encoded data slices to produce a data segment, encoding thedata segment to produce a rebuilt encoded data slice, storing therebuilt encoded data slice, and resetting the error flag correspondingto the slice name of the encoded data slice. The method repeats backstep 378.

FIG. 17A is a flowchart illustrating another example of rebuilding datastored in a dispersed storage network (DSN), which includes similarsteps to FIG. 16. The method begins with step 378 of FIG. 16 where aprocessing module (e.g., a dispersed storage (DS) processing unit, a DSunit) detects a slice error of an encoded data slice. The methodcontinues at step 390 where the processing module determines a number ofslice errors of a set of encoded data slices that includes the encodeddata slice. The determining may be based on one or more of obtainingslice names of the set of encoded data slices based on a slice name ofthe encoded data slice, querying DS units associated with the set ofencoded data slices, and retrieving one or more slice error flagsassociated with the set of encoded data slices.

The method continues at step 392 where the processing module determineswhether to rebuild the encoded data slice based on the number of sliceerrors. The determining may be based on one or more of comparing thenumber of slice errors to an error threshold, determining whether thecomparison is favorable, and indicating to rebuild when the comparisonis not favorable. For example, the processing module determines that thecomparison is favorable when the number of slice errors is greater thanthe error threshold. The error threshold may range from one to n−k,wherein n=a pillar width and k=a decode threshold. For example, theerror threshold may be set to just one slice error to provide a higherlevel of reliability. As another example, the error threshold may be setto 6 (e.g., 6=n−k, when the pillar width=16 and the decode threshold=10)to avoid utilizing system resources to rebuild the encoded data slice.

The method repeats back to step 378 of FIG. 16 when the processingmodule determines to not to rebuild the encoded data slice. The methodcontinues to step 386 of FIG. 16 when the processing module determinesto rebuild the encoded data slice. The method continues at step 386 ofFIG. 16 where the processing module facilitates rebuilding of theencoded data slice. The method repeats back to step 378 of FIG. 16 wherethe processing module detects the slice error to look for furthererrors.

FIG. 17B is a flowchart illustrating another example of rebuilding datastored in a dispersed storage network (DSN), which includes similarsteps to FIGS. 15, 16, and 17A. The method begins with step 378 of FIG.16 where a processing module (e.g., a dispersed storage (DS) processingunit, a DS unit) detects a slice error of an encoded data slice. Themethod continues with step 390 of FIG. 17A where the processing moduledetermines a number of slice errors of a set of encoded data slices thatincludes the encoded data slice. The method continues with steps 370-372of FIG. 15 where the processing module obtains a slice priority levelindicator of the encoded data slice and obtains a timestamp associatedwith the encoded data slice.

The method continues at step 404 where the processing module determineswhether to rebuild the encoded data slice based on the number of sliceerrors, the slice priority level indicator, and the timestamp. Forexample, the processing module determines to rebuild the encoded dataslice when the number of slice errors is greater than a rebuildthreshold corresponding to the slice priority level and an amount ofelapsed time since the timestamp is less than a time thresholdcorresponding to the priority level. The method repeats back to step 378of FIG. 16 when the processing module determines not rebuild the encodeddata slice. The method continues to step 386 of FIG. 16 when theprocessing module determines to rebuild the encoded data slice. Themethod continues with step 386 of FIG. 16 where the processing modulefacilitates rebuilding of the encoded data slice. The method repeatsback to step 378 of FIG. 16 to look for further errors.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “operably coupled to”, “coupled to”, and/or “coupling” includesdirect coupling between items and/or indirect coupling between items viaan intervening item (e.g., an item includes, but is not limited to, acomponent, an element, a circuit, and/or a module) where, for indirectcoupling, the intervening item does not modify the information of asignal but may adjust its current level, voltage level, and/or powerlevel. As may further be used herein, inferred coupling (i.e., where oneelement is coupled to another element by inference) includes direct andindirect coupling between two items in the same manner as “coupled to”.As may even further be used herein, the term “operable to” or “operablycoupled to” indicates that an item includes one or more of powerconnections, input(s), output(s), etc., to perform, when activated, oneor more its corresponding functions and may further include inferredcoupling to one or more other items. As may still further be usedherein, the term “associated with”, includes direct and/or indirectcoupling of separate items and/or one item being embedded within anotheritem. As may be used herein, the term “compares favorably”, indicatesthat a comparison between two or more items, signals, etc., provides adesired relationship. For example, when the desired relationship is thatsignal 1 has a greater magnitude than signal 2, a favorable comparisonmay be achieved when the magnitude of signal 1 is greater than that ofsignal 2 or when the magnitude of signal 2 is less than that of signal1.

As may also be used herein, the terms “processing module”, “processingcircuit”, and/or “processing unit” may be a single processing device ora plurality of processing devices. Such a processing device may be amicroprocessor, micro-controller, digital signal processor,microcomputer, central processing unit, field programmable gate array,programmable logic device, state machine, logic circuitry, analogcircuitry, digital circuitry, and/or any device that manipulates signals(analog and/or digital) based on hard coding of the circuitry and/oroperational instructions. The processing module, module, processingcircuit, and/or processing unit may be, or further include, memoryand/or an integrated memory element, which may be a single memorydevice, a plurality of memory devices, and/or embedded circuitry ofanother processing module, module, processing circuit, and/or processingunit. Such a memory device may be a read-only memory, random accessmemory, volatile memory, non-volatile memory, static memory, dynamicmemory, flash memory, cache memory, and/or any device that storesdigital information. Note that if the processing module, module,processing circuit, and/or processing unit includes more than oneprocessing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

The present invention has been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claimed invention. Further, theboundaries of these functional building blocks have been arbitrarilydefined for convenience of description. Alternate boundaries could bedefined as long as the certain significant functions are appropriatelyperformed. Similarly, flow diagram blocks may also have been arbitrarilydefined herein to illustrate certain significant functionality. To theextent used, the flow diagram block boundaries and sequence could havebeen defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claimed invention. One of average skill in the artwill also recognize that the functional building blocks, and otherillustrative blocks, modules and components herein, can be implementedas illustrated or by discrete components, application specificintegrated circuits, processors executing appropriate software and thelike or any combination thereof.

The present invention may have also been described, at least in part, interms of one or more embodiments. An embodiment of the present inventionis used herein to illustrate the present invention, an aspect thereof, afeature thereof, a concept thereof, and/or an example thereof. Aphysical embodiment of an apparatus, an article of manufacture, amachine, and/or of a process that embodies the present invention mayinclude one or more of the aspects, features, concepts, examples, etc.described with reference to one or more of the embodiments discussedherein. Further, from figure to figure, the embodiments may incorporatethe same or similarly named functions, steps, modules, etc. that may usethe same or different reference numbers and, as such, the functions,steps, modules, etc. may be the same or similar functions, steps,modules, etc. or different ones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of the various embodimentsof the present invention. A module includes a processing module, afunctional block, hardware, and/or software stored on memory forperforming one or more functions as may be described herein. Note that,if the module is implemented via hardware, the hardware may operateindependently and/or in conjunction software and/or firmware. As usedherein, a module may contain one or more sub-modules, each of which maybe one or more modules.

While particular combinations of various functions and features of thepresent invention have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent invention is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by one or more computingdevices of a dispersed storage network (DSN), the method comprises: as aplurality of data objects is ingested, determining, for each data objectof at least some of the plurality of data objects, a priority indicatorto produce a listing of priority indicators corresponding to the atleast some of the plurality of data objects; for a data object of the atleast some of the plurality of data objects: determining dispersedstorage error encoding parameters based on a corresponding priorityindicator of the listing of priority indicators; dispersed storage errorencoding the data object in accordance with the dispersed storage errorencoding parameters to produce a plurality of sets of encoded dataslices; and facilitating storage of the plurality of sets of encodeddata slices in memory of the DSN; identifying a first data object of theat least some of the plurality of data objects for analysis based on acorresponding priority indicator of the first data object and ananalysis priority; dispersed storage error decoding a first plurality ofsets of encoded data slices to recover the first data object; analyzingthe recovered first data object in accordance with analysis criteria todetermine relevancy of the first data object; and when the relevancy ofthe first data object is below a threshold, issuing a command to deletethe first plurality of sets of encoded data slices.
 2. The method ofclaim 1 further comprises: when the relevancy of the first data objectis above the threshold, updating the corresponding priority indicator ofthe first data object.
 3. The method of claim 1 further comprises:ingesting the plurality of data objects during an ingest time period;establishing an analysis time period during which time at least higherpriority data objects of the at least some of the plurality of dataobjects will be analyzed; and determining, for the data object of the atleast some of the plurality of data objects, the priority indicatorbased on the analysis time period, the quantity of data objects of theat least some of the plurality of data objects, and previouslydetermined priority indicators of other data objects of the at leastsome of the plurality of data objects.
 4. The method of claim 1, whereinthe determining the priority indicator for the data object of the atleast some of the plurality of data objects comprises: as the dataobject of the at least some of the plurality of data objects is beingingested, identifying one or more data characteristics of the dataobject, wherein the one or more data characteristics are from a list ofdata characteristics, wherein the list of data characteristics includesa data source factor, a data content factor, and a data locationorigination factor.
 5. The method of claim 1, wherein the determiningdispersed storage error encoding parameters comprises: establishing alikelihood of analysis for the data object based on an ingest timeperiod, an analysis time period, the priority indicator of the dataobject, and priority indicators of other data objects of the at leastsome of the plurality of data objects; when the likelihood of analysisis high, establishing the dispersed storage error encoding parametershaving a first pillar width number and a first decode threshold number;and when the likelihood of analysis is low, establishing the dispersedstorage error encoding parameters having a second pillar width numberand a second decode threshold number, wherein the second pillar widthnumber is greater than the first pillar width number and wherein thesecond decode threshold number is greater than the first decodethreshold number.
 6. The method of claim 5 further comprises: as ananalysis time period passes and when the likelihood of analysis is low,incrementally deleting an encoded data slice from one or more sets ofencoded data slices of the plurality of sets of encoded data slicesuntil the analysis time period expires, the data object is analyzed, orthe second decode threshold number of encoded data slices of the one ormore sets of encoded data slices of the plurality of sets of encodeddata slices is reached; and when the analysis time period expires andthe data object has not been analyzed, deleting remaining encoded dataslices of the plurality of sets of encoded data slices.
 7. The method ofclaim 1, wherein the analysis priority comprises one or more factorsfrom a list of factors, wherein the list of factors includes: likelihoodof the data object including a search term; likelihood of the dataobject including a character string; identity of a source of the dataobject; identity of a destination of the data object; likelihood of thedata object including a data pattern; identity of a location from whichthe data object was originated; identity of a location to which the dataobject was sent; and timing of when the data object was originated,transmitted, received, or stored.
 8. A computer readable memorycomprises: a first storage memory section that stores operationalinstructions that, when read by a first computing device, causes thefirst computing device to: as a plurality of data objects is ingested,determine, for each data object of at least some of the plurality ofdata objects, a priority indicator to produce a listing of priorityindicators corresponding to the at least some of the plurality of dataobjects; and for a data object of the at least some of the plurality ofdata objects: determine dispersed storage error encoding parametersbased on a corresponding priority indicator of the listing of priorityindicators; dispersed storage error encode the data object in accordancewith the dispersed storage error encoding parameters to produce aplurality of sets of encoded data slices; and facilitate storage of theplurality of sets of encoded data slices in memory of the DSN; and asecond storage memory section that stores operational instructions that,when read by the first computing device or a second computing device,causes the first or the second computing device to: identify a firstdata object of the at least some of the plurality of data objects foranalysis based on a corresponding priority indicator of the first dataobject and an analysis priority; dispersed storage error decode a firstplurality of sets of encoded data slices to recover the first dataobject; analyze the recovered first data object in accordance withanalysis criteria to determine relevancy of the first data object; andwhen the relevancy of the first data object is below a threshold, issuea command to delete the first plurality of sets of encoded data slices.9. The computer readable memory of claim 8 comprises: the second storagememory section further stores operational instructions that, when readby the first computing device or the second computing device, causes thefirst or the second computing device to: when the relevancy of the firstdata object is above the threshold, update the corresponding priorityindicator of the first data object.
 10. The computer readable memory ofclaim 8 comprises: ingesting the plurality of data objects during aningest time period; the first storage memory section further storesoperational instructions that, when read by the first computing device,causes the first computing device to: establish an analysis time periodduring which time at least higher priority data objects of the at leastsome of the plurality of data objects will be analyzed; and determine,for the data object of the at least some of the plurality of dataobjects, the priority indicator based on the analysis time period, thequantity of data objects of the at least some of the plurality of dataobjects, and previously determined priority indicators of other dataobjects of the at least some of the plurality of data objects.
 11. Thecomputer readable memory of claim 8, wherein the first storage memorysection further stores operational instructions that, when read by thefirst computing device, causes the first computing device to determinethe priority indicator for the data object of the at least some of theplurality of data objects by: as the data object of the at least some ofthe plurality of data objects is being ingested, identifying one or moredata characteristics of the data object, wherein the one or more datacharacteristics are from a list of data characteristics, wherein thelist of data characteristics includes a data source factor, a datacontent factor, and a data location origination factor.
 12. The computerreadable memory of claim 8, wherein the first storage memory sectionfurther stores operational instructions that, when read by the firstcomputing device, causes the first computing device to determine thedispersed storage error encoding parameters by: establishing alikelihood of analysis for the data object based on an ingest timeperiod, an analysis time period, the priority indicator of the dataobject, and priority indicators of other data objects of the at leastsome of the plurality of data objects; when the likelihood of analysisis high, establishing the dispersed storage error encoding parametershaving a first pillar width number and a first decode threshold number;and when the likelihood of analysis is low, establishing the dispersedstorage error encoding parameters having a second pillar width numberand a second decode threshold number, wherein the second pillar widthnumber is greater than the first pillar width number and wherein thesecond decode threshold number is greater than the first decodethreshold number.
 13. The computer readable memory of claim 12 furthercomprises: the second storage memory section further stores operationalinstructions that, when read by the first computing device or the secondcomputing device, causes the first or the second computing device to: asan analysis time period passes and when the likelihood of analysis islow, incrementally facilitating deleting an encoded data slice from oneor more sets of encoded data slices of the plurality of sets of encodeddata slices until the analysis time period expires, the data object isanalyzed, or the second decode threshold number of encoded data slicesof the one or more sets of encoded data slices of the plurality of setsof encoded data slices is reached; and when the analysis time periodexpires and the data object has not been analyzed, facilitating deletingremaining encoded data slices of the plurality of sets of encoded dataslices.
 14. The computer readable memory of claim 8, wherein theanalysis priority comprises one or more factors from a list of factors,wherein the list of factors includes: likelihood of the data objectincluding a search term; likelihood of the data object including acharacter string; identity of a source of the data object; identity of adestination of the data object; likelihood of the data object includinga data pattern; identity of a location from which the data object wasoriginated; identity of a location to which the data object was sent;and timing of when the data object was originated, transmitted,received, or stored.